Updated on 2026/01/27

写真a

 
MATSUSHIMA, Toshiyasu
 
Affiliation
Faculty of Science and Engineering, School of Fundamental Science and Engineering
Job title
Professor
Degree
博士(工学) ( 早稲田大学 )
Engineering
Homepage URL
http://www.matsu.mgmt.waseda.ac.jp/users/www/index.html

Education Background

  • 　
    -
    1991

    Waseda University   Graduate School, Division of Science and Engineering  

  • 　
    -
    1978

    Waseda University   Faculty of Science and Engineering  

Professional Memberships

  • 　
    　
    　

    日本応用数理学会

  • 　
    　
    　

    応用統計学会

  • 　
    　
    　

    日本OR学会

  • 　
    　
    　

    品質管理学会

  • 　
    　
    　

    人工知能学会

  • 　
    　
    　

    情報処理学会

  • 　
    　
    　

    情報理論とその応用学会

  • 　
    　
    　

    IEEE

  • 　
    　
    　

    電子情報通信学会

▼display all

Research Areas

  • Applied mathematics and statistics / Basic mathematics / Information security / Control and system engineering / Intelligent informatics / Statistical science / Theory of informatics / Communication and network engineering

Research Interests

  • 情報理論、符号理論、統計科学、学習理論、知能情報、データ科学，情報セキュリティ

 

Papers

  • Necessary and Sufficient Conditions for Capacity-Achieving Private Information Retrieval with Adversarial Servers.

    Atsushi Miki, Toshiyasu Matsushima

    CoRR   abs/2511.06003  2025.11

    DOI

  • A Lower Bound for the Number of Linear Regions of Ternary ReLU Regression Neural Networks.

    Yuta Nakahara, Manabu Kobayashi, Toshiyasu Matsushima

    CoRR   abs/2507.16079  2025.07

    DOI

  • Meta-Tree: Bayesian Approach to Avoid Overfitting in Decision Trees and Analysis on the Application to Boosting.

    Naoki Ichijo, Toshiyasu Matsushima

    MLSP     1 - 6  2025

    DOI

    Scopus

  • A New Framework for Causal Inference Without Missing Data Analysis: Bayes Optimal Treatment Effect Estimation.

    Kohei Horinouchi, Shimpei Onishi, Toshiyasu Matsushima

    DSAA     1 - 5  2025

    DOI

  • Bayesian Decision Theory on Decision Trees: Uncertainty Evaluation and Interpretability.

    Yuta Nakahara, Shota Saito, Naoki Ichijo, Koki Kazama, Toshiyasu Matsushima

    International Conference on Artificial Intelligence and Statistics(AISTATS)     1045 - 1053  2025

  • An Efficient Bayes Coding Algorithm for Changing Context Tree Model

    Koshi SHIMADA, Shota SAITO, Toshiyasu MATSUSHIMA

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E107.A ( 3 ) 448 - 457  2024.03

    DOI

  • Batch Updating of a Posterior Tree Distribution Over a Meta-Tree

    Yuta NAKAHARA, Toshiyasu MATSUSHIMA

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E107.A ( 3 ) 523 - 525  2024.03

    DOI

  • Necessary and Sufficient Conditions for Capacity-Achieving Private Information Retrieval with Non-Colluding and Colluding Servers.

    Atsushi Miki, Yusuke Morishita, Toshiyasu Matsushima

    CoRR   abs/2404.13624  2024

    DOI

  • An Algorithmic Framework for Constructing Multiple Decision Trees by Evaluating Their Combination Performance Throughout the Construction Process.

    Keito Tajima, Naoki Ichijo, Yuta Nakahara, Toshiyasu Matsushima

    CoRR   abs/2402.06452  2024

    DOI

  • Boosting-Based Sequential Meta-Tree Ensemble Construction for Improved Decision Trees.

    Ryota Maniwa, Naoki Ichijo, Yuta Nakahara, Toshiyasu Matsushima

    CoRR   abs/2402.06386  2024

    DOI

  • An Algorithmic Framework for Constructing Multiple Decision Trees by Evaluating Their Combination Performance Throughout the Construction Process.

    Keito Tajima, Naoki Ichijo, Yuta Nakahara, Koshi Shimada, Toshiyasu Matsushima

    IEEE International Conference on Systems, Man, and Cybernetics(SMC)     3390 - 3396  2024

    DOI

  • Necessary and Sufficient Conditions for Capacity-Achieving Private Information Retrieval and Its Construction Method.

    Atsushi Miki, Yusuke Morishita, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     395 - 400  2024

    DOI

    Scopus

  • An Efficient Image Segmentation Algorithm Based on Bayes Decision Theory and its Application for Region Detection.

    Yilun Wang 0003, Koshi Shimada, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     206 - 211  2024

    DOI

    Scopus

  • Bayesian Decision-Theoretic Prediction with Ensemble of Meta-Trees for Classification Problems.

    Naoki Ichijo, Ryota Maniwa, Yuta Nakahara, Koshi Shimada, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     70 - 74  2024

    DOI

    Scopus

  • Hyperparameter Learning of Bayesian Context Tree Models.

    Yuta Nakahara, Shota Saito, Koshi Shimada, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)     537 - 542  2023.06

    DOI

    Scopus

  • Non-Asymptotic Bounds of Cumulant Generating Function of Codeword Lengths in Variable-Length Lossy Compression.

    Shota Saito, Toshiyasu Matsushima

    IEEE Transactions on Information Theory   69 ( 4 ) 2113 - 2119  2023.04

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Asymptotic Evaluation of Classification in the Presence of Label Noise

    Goki Yasuda, Tota Suko, Manabu Kobayashi, Toshiyasu Matsushima

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E106A ( 3 ) 422 - 430  2023.03

    　View Summary

    In a practical classification problem, there are cases where incorrect labels are included in training data due to label noise. We introduce a classification method in the presence of label noise that idealizes a classification method based on the expectation-maximization (EM) algorithm, and evaluate its performance theoretically. Its performance is asymptotically evaluated by assessing the risk function defined as the Kullback-Leibler divergence between predictive distribution and true distribution. The result of this performance evaluation enables a theoretical evaluation of the most successful performance that the EM-based classification method may achieve.

    DOI

    Scopus

  • Prediction Algorithms Achieving Bayesian Decision Theoretical Optimality Based on Decision Trees as Data Observation Processes.

    Yuta Nakahara, Shota Saito, Naoki Ichijo, Koki Kazama, Toshiyasu Matsushima

    CoRR   abs/2306.07060  2023

    DOI

  • A Generalization of the Stratonovich's Value of Information and Application to Privacy-Utility Trade-off.

    Akira Kamatsuka, Takahiro Yoshida, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)   abs/2201.11449   1999 - 2004  2022.06

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Stochastic Model of Block Segmentation Based on Improper Quadtree and Optimal Code under the Bayes Criterion

    Yuta Nakahara, Toshiyasu Matsushima

    2022 Data Compression Conference (DCC)   24 ( 8 ) 1152 - 1152  2022.03  [International journal]

    　View Summary

    Most previous studies on lossless image compression have focused on improving preprocessing functions to reduce the redundancy of pixel values in real images. However, we assumed stochastic generative models directly on pixel values and focused on achieving the theoretical limit of the assumed models. In this study, we proposed a stochastic model based on improper quadtrees. We theoretically derive the optimal code for the proposed model under the Bayes criterion. In general, Bayes-optimal codes require an exponential order of calculation with respect to the data lengths. However, we propose an algorithm that takes a polynomial order of calculation without losing optimality by assuming a novel prior distribution.

    DOI PubMed

  • The Ratio of the Desired Parameters of Deep Neural Networks

    Yasushi ESAKI, Yuta NAKAHARA, Toshiyasu MATSUSHIMA

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E105.A ( 3 ) 433 - 435  2022.03

    DOI

  • Upper Bound on Privacy-Utility Tradeoff Allowing Positive Excess Distortion Probability

    Shota SAITO, Toshiyasu MATSUSHIMA

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E105.A ( 3 ) 425 - 427  2022.03

    DOI

  • Probability Distribution on Full Rooted Trees

    Yuta Nakahara, Shota Saito, Akira Kamatsuka, Toshiyasu Matsushima

    Entropy   24 ( 3 ) 328 - 328  2022.02  [International journal]

    　View Summary

    The recursive and hierarchical structure of full rooted trees is applicable to statistical models in various fields, such as data compression, image processing, and machine learning. In most of these cases, the full rooted tree is not a random variable; as such, model selection to avoid overfitting is problematic. One method to solve this problem is to assume a prior distribution on the full rooted trees. This enables the optimal model selection based on Bayes decision theory. For example, by assigning a low prior probability to a complex model, the maximum a posteriori estimator prevents the selection of the complex one. Furthermore, we can average all the models weighted by their posteriors. In this paper, we propose a probability distribution on a set of full rooted trees. Its parametric representation is suitable for calculating the properties of our distribution using recursive functions, such as the mode, expectation, and posterior distribution. Although such distributions have been proposed in previous studies, they are only applicable to specific applications. Therefore, we extract their mathematically essential components and derive new generalized methods to calculate the expectation, posterior distribution, etc.

    DOI PubMed

    Scopus

    13
    Citation
    (Scopus)

  • Stochastic 2D Signal Generative Model with Wavelet Packets Basis Regarded as a Random Variable and Bayes Optimal Processing.

    Ryohei Oka, Yuta Nakahara, Toshiyasu Matsushima

    CoRR   abs/2202.00568  2022

  • Probability Distribution on Rooted Trees.

    Yuta Nakahara, Shota Saito, Akira Kamatsuka, Toshiyasu Matsushima

    CoRR   abs/2201.09460  2022

  • A Group-Type Distributed Coded Computation Scheme Based on a Gabidulin Code.

    Koki Kazama, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     174 - 178  2022

  • A Group-Type Distributed Secure Coded Computation Scheme Based on a Secret Sharing.

    Koki Kazama, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     154 - 158  2022

  • Two-dimensional Autoregressive Model with Time-varying Parameters and the Bayes Codes.

    Yuta Nakahara, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     149 - 153  2022

  • Probability Distribution on Rooted Trees.

    Yuta Nakahara, Shota Saito, Akira Kamatsuka, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)   2022-June   174 - 179  2022

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • An Algorithm for Computing the Stratonovich's Value of Information.

    Akira Kamatsuka, Takahiro Yoshida, Koki Kazama, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)   abs/2205.02778   89 - 93  2022

    DOI

  • Bayes Optimal Estimation and Its Approximation Algorithm for Difference with and without Treatment under URLC Model.

    Taisuke Ishiwatari, Shota Saito, Yuta Nakahara, Yuji Iikubo, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     144 - 148  2022

    DOI

    Scopus

  • Hyperparameter Learning of Stochastic Image Generative Models with Bayesian Hierarchical Modeling and Its Effect on Lossless Image Coding.

    Yuta Nakahara, Toshiyasu Matsushima

    IEEE Information Theory Workshop(ITW)     1 - 6  2021.10

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Privacy-Utility Trade-off with the Stratonovich's Value of Information.

    Akira Kamatsuka, Takahiro Yoshida, Toshiyasu Matsushima

    IEEE Information Theory Workshop(ITW)     1 - 6  2021.10

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Cluster’s Number Free Bayes Prediction of General Framework on Mixture of Regression Models

    Haruka Murayama, Shota Saito, Yuji Iikubo, Yuta Nakahara, Toshiyasu Matsushima

    Journal of Statistical Theory and Applications   20 ( 3 ) 425 - 449  2021.09

    　View Summary

    <title>Abstract</title>Prediction based on a single linear regression model is one of the most common way in various field of studies. It enables us to understand the structure of data, but might not be suitable to express the data whose structure is complex. To express the structure of data more accurately, we make assumption that the data can be divided in clusters, and has a linear regression model in each cluster. In this case, we can assume that each explanatory variable has their own role; explaining the assignment to the clusters, explaining the regression to the target variable, or being both of them. Introducing probabilistic structure to the data generating process, we derive the optimal prediction under Bayes criterion and the algorithm which calculates it sub-optimally with variational inference method. One of the advantages of our algorithm is that it automatically weights the probabilities of being each number of clusters in the process of the algorithm, therefore it solves the concern about selection of the number of clusters. Some experiments are performed on both synthetic and real data to demonstrate the above advantages and to discover some behaviors and tendencies of the algorithm.

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Evaluation of Error Probability of Classification Based on the Analysis of the Bayes Code: Extension and Example.

    Shota Saito, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)   2021-   1445 - 1450  2021.07

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Meta-Tree Random Forest: Probabilistic Data-Generative Model and Bayes Optimal Prediction

    Nao Dobashi, Shota Saito, Yuta Nakahara, Toshiyasu Matsushima

    Entropy   23 ( 6 ) 768 - 768  2021.06  [International journal]

    　View Summary

    This paper deals with a prediction problem of a new targeting variable corresponding to a new explanatory variable given a training dataset. To predict the targeting variable, we consider a model tree, which is used to represent a conditional probabilistic structure of a targeting variable given an explanatory variable, and discuss statistical optimality for prediction based on the Bayes decision theory. The optimal prediction based on the Bayes decision theory is given by weighting all the model trees in the model tree candidate set, where the model tree candidate set is a set of model trees in which the true model tree is assumed to be included. Because the number of all the model trees in the model tree candidate set increases exponentially according to the maximum depth of model trees, the computational complexity of weighting them increases exponentially according to the maximum depth of model trees. To solve this issue, we introduce a notion of meta-tree and propose an algorithm called MTRF (Meta-Tree Random Forest) by using multiple meta-trees. Theoretical and experimental analyses of the MTRF show the superiority of the MTRF to previous decision tree-based algorithms.

    DOI PubMed

    Scopus

    13
    Citation
    (Scopus)

  • Probability Distribution on Full Rooted Trees.

    Yuta Nakahara, Shota Saito, Akira Kamatsuka, Toshiyasu Matsushima

    CoRR   abs/2109.12825  2021

  • A Stochastic Model for Block Segmentation of Images Based on the Quadtree and the Bayes Code for It.

    Yuta Nakahara, Toshiyasu Matsushima

    CoRR   abs/2106.03349  2021

  • An Efficient Bayes Coding Algorithm for the Non-Stationary Source in Which Context Tree Model Varies from Interval to Interval.

    Koshi Shimada, Shota Saito, Toshiyasu Matsushima

    CoRR   abs/2105.05163  2021

  • An Efficient Bayes Coding Algorithm for the Non-Stationary Source in Which Context Tree Model Varies from Interval to Interval.

    Koshi Shimada, Shota Saito, Toshiyasu Matsushima

    IEEE Information Theory Workshop(ITW)     1 - 6  2021

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • A Stochastic Model for Block Segmentation of Images Based on the Quadtree and the Bayes Code for It.

    Yuta Nakahara, Toshiyasu Matsushima

    Entropy   23 ( 8 ) 991 - 991  2021

    DOI

    Scopus

    10
    Citation
    (Scopus)

  • Theoretical Analysis of the Advantage of Deepening Neural Networks.

    Yasushi Esaki, Yuta Nakahara, Toshiyasu Matsushima

    19th IEEE International Conference on Machine Learning and Applications(ICMLA)   abs/2009.11479   479 - 484  2020.12

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Analysis of decoding error probability of spatially "Mt. Fuji" coupled LDPC codes inwaterfall region of the BEC

    Yuta NAKAHARA, Toshiyasu MATSUSHIMA

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E103A ( 12 ) 1337 - 1346  2020.12

    DOI

    Scopus

  • A bayesian decision-theoretic change-point detection for i.p.i.d. sources

    Kairi Suzuki, Akira Kamatsuka, Toshiyasu Matsushima

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E103A ( 12 ) 1393 - 1402  2020.12

    DOI

    Scopus

  • On Two Information Quantities Relating Two Distortion Balls.

    Shota Saito, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     16 - 20  2020.10

  • Autoregressive Image Generative Models with Normal and t-distributed Noise and the Bayes Codes for Them.

    Yuta Nakahara, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     81 - 85  2020.10

  • A Note on a Relationship between Smooth Locally Decodable Codes and Private Information Retrieval

    Koki Kazama, Akira Kamatsuka, Takahiro Yoshida, Toshiyasu Matsushima

    Proceedings of 2020 International Symposium on Information Theory and its Applications, ISITA 2020     259 - 263  2020.10

    　View Summary

    We focus on smooth locally decodable codes (SLDC) and Private Information Retrieval (PIR). Recently, a relationship between SLDC and PIR are studied using information theoretical notations. In this paper, we clarify a relationship between SLDCs and PIR using set theoretical notations mainly.

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • A Note on a Relationship between Smooth Locally Decodable Codes and Private Information Retrieval

    Koki Kazama, Akira Kamatsuka, Takahiro Yoshida, Toshiyasu Matsushima

    IEICE Proceeding Series   65   259 - 263  2020.10

    　View Summary

    We focus on smooth locally decodable codes (SLDC) and Private Information Retrieval (PIR). Recently, a relationship between SLDC and PIR are studied using information theoretical notations. In this paper, we clarify a relationship between SLDCs and PIR using set theoretical notations mainly.

    DOI CiNii

  • Evaluation of Error Probability of Classification Based on the Analysis of the Bayes Code.

    Shota Saito, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)   2020-   2510 - 2514  2020.06

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Bayes code for two-dimensional auto-regressive hidden Markov model and its application to lossless image compression

    Yuta Nakahara, Toshiyasu Matsushima

    International Workshop on Advanced Imaging Technology (IWAIT) 2020    2020.06

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • A Statistical Decision-Theoretic Approach for Measuring Privacy Risk and Utility in Databases

    Alisa Miyashita, Akira Kamatsuka, Takahiro Yoshida, Toshiyasu Matsushima

    2020 54th Annual Conference on Information Sciences and Systems, CISS 2020     1 - 6  2020.03

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • A Stochastic Model of Block Segmentation Based on the Quadtree and the Bayes Code for It

    Yuta Nakahara, Toshiyasu Matsushima

    2020 Data Compression Conference (DCC)   23 ( 8 ) 293 - 302  2020.03  [International journal]

    　View Summary

    In information theory, lossless compression of general data is based on an explicit assumption of a stochastic generative model on target data. However, in lossless image compression, researchers have mainly focused on the coding procedure that outputs the coded sequence from the input image, and the assumption of the stochastic generative model is implicit. In these studies, there is a difficulty in discussing the difference between the expected code length and the entropy of the stochastic generative model. We solve this difficulty for a class of images, in which they have non-stationarity among segments. In this paper, we propose a novel stochastic generative model of images by redefining the implicit stochastic generative model in a previous coding procedure. Our model is based on the quadtree so that it effectively represents the variable block size segmentation of images. Then, we construct the Bayes code optimal for the proposed stochastic generative model. It requires the summation of all possible quadtrees weighted by their posterior. In general, its computational cost increases exponentially for the image size. However, we introduce an efficient algorithm to calculate it in the polynomial order of the image size without loss of optimality. As a result, the derived algorithm has a better average coding rate than that of JBIG.

    DOI PubMed

  • A Note on a Relationship between Smooth Locally Decodable Codes and Private Information Retrieval.

    Koki Kazama, Akira Kamatsuka, Takahiro Yoshida, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     259 - 263  2020

  • A Note on Mixed Level Experimental Designs Using Augmented Orthogonal Arrays

    Junki Yamaguchi, Koki Kazama, Akira Kamatsuka, Shota Saito, Toshiyasu Matsushima

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   J103-A ( 1 )  2020.01  [Refereed]

    J-GLOBAL

  • Reducing the Computational and Communication Complexity of a Distributed Optimization for Regularized Logistic Regression.

    Nozomi Miya, Hideyuki Masui, Hajime Jinushi, Toshiyasu Matsushima

    2019 IEEE International Conference on Systems, Man and Cybernetics(SMC)     3454 - 3459  2019.10  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Model Selection of Bayesian Hierarchical Mixture of Experts based on Variational Inference.

    Yuji Iikubo, Shunsuke Horii, Toshiyasu Matsushima

    2019 IEEE International Conference on Systems, Man and Cybernetics(SMC)     3474 - 3479  2019.10  [Refereed]

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Covariance Evolution for Spatially "Mt. Fuji" Coupled LDPC Codes.

    Yuta Nakahara, Toshiyasu Matsushima

    2019 IEEE Information Theory Workshop(ITW)   abs/1904.05396   1 - 5  2019.08  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Non-Asymptotic Fundamental Limits of Guessing Subject to Distortion.

    Shota Saito, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)   abs/1808.06190   652 - 656  2019.07  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Distributed Stochastic Gradient Descent Using LDGM Codes.

    Shunsuke Horii, Takahiro Yoshida, Manabu Kobayashi, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)   abs/1901.04668   1417 - 1421  2019.07  [Refereed]

    DOI

    Scopus

    12
    Citation
    (Scopus)

  • Variable-Length Intrinsic Randomness on Two Performance Criteria based on Variational Distance

    Jun Yoshizawa, Shota Saito, Toshiyasu Matsushima

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E102-A ( 12 ) 1642 - 1650  2019  [Refereed]

    DOI

    Scopus

  • Probabilistic fault diagnosis and its analysis in multicomputer systems

    Manabu Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E101A ( 12 ) 2072 - 2081  2018.12

    DOI

    Scopus

  • A Note on a Bound on the Rate of a Locally Recoverable Code with Multiple Recovering Sets

    Koki Kazama, Akira Kamatsuka, Takahiro Yoshida, Toshiyasu Matsushima

    IEICE Proceeding Series   55   520 - 520  2018.10

    　View Summary

    A locally recoverable code (LRC code) is a code such that each codeword symbol can be recovered from other codeword symbols. In this research, we propose one possible generalization of previous LRC codes and we derive a bound on the rate of the proposed code.

    DOI CiNii

  • Variable-Length Intrinsic Randomness Allowing Positive Value of the Average Variational Distance.

    Jun Yoshizawa, Shota Saito, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)   abs/1801.01699   354 - 358  2018

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Linear Programming Bounds for Multi-level Unequal Protection Codes.

    Tomohiko Saito, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE International Conference on Systems, Man, and Cybernetics(SMC)     2917 - 2922  2018

    DOI

    Scopus

  • New Results on Variable-Length Lossy Compression Allowing Positive Overflow and Excess Distortion Probabilities.

    Shota Saito, Hideki Yagi, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     359 - 363  2018

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Sparse Bayesian Hierarchical Mixture of Experts and Variational Inference.

    Yuji Iikubo, Shunsuke Horii, Toshiyasu Matsushima

    International Symposium on Information Theory and Its Applications(ISITA)     60 - 64  2018

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Bayesian Independent Component Analysis under Hierarchical Model on Independent Components

    Asaba, Kai, Saito, Shota, Horii, Shunsuke, Matsushima, Toshiyasu

    Proceedings of 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018     959 - 962  2018

    DOI

    Scopus

  • Cumulant Generating Function of Codeword Lengths in Variable-Length Lossy Compression Allowing Positive Excess Distortion Probability.

    Shota Saito, Toshiyasu Matsushima

    2018 IEEE International Symposium on Information Theory(ISIT)   abs/1801.02496   881 - 885  2018

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • A Note on Weight Distributions of Spatially "Mt. Fuji" Coupled LDPC Codes.

    Nakahara, Yuta, Matsushima, Toshiyasu

    IEICE Transactions   vol. 101-A ( 12 ) 2194 - 2198  2018

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • 推薦システムの新規顧客問題における半教師付き学習

    前田康成, 山内翔, 鈴木正清, 松嶋敏泰

    バイオメディカル・ファジィ・システム学会誌   20 ( 1 ) 37 - 46  2018

  • 顧客クラスが変化する推薦システムにおける半教師付き学習

    前田康成, 山内翔, 鈴木正清, 松嶋敏泰

    バイオメディカル・ファジィ・システム学会誌   20 ( 1 ) 15 - 22  2018

  • 推薦システムにおける新規顧客問題に関する一考察

    前田康成, 山内翔, 鈴木正清, 松嶋敏泰

    バイオメディカル・ファジィ・システム学会誌   Vol.19 ( 2 ) 21 - 27  2017.12  [Refereed]

  • マルコフ決定過程を用いたヘルスケア支援に関する一考察

    前田康成, 山内翔, 鈴木正清, 高野賢裕, 松嶋敏泰

    バイオメディカル・ファジィ・システム学会誌   Vol.19 ( 2 ) 21 - 27  2017.12  [Refereed]

  • Collaborative Filtering Based on the Latent Class Model for Attributes.

    Manabu Kobayashi, Kenta Mikawa, Masayuki Goto, Toshiyasu Matsushima, Shigeichi Hirasawa

    16th IEEE International Conference on Machine Learning and Applications(ICMLA)   ( 893 ) 893 - 896  2017.12  [Refereed]

    DOI

    Scopus

  • Spatially "Mt. Fuji" Coupled LDPC codes

    Yuta Nakahara, Shota Saito, Toshiyasu Matsushima

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E100A ( 12 ) 2594 - 2606  2017.12

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Evaluation of overflow probability of bayes code in moderate deviation regime

    Shota Saito, Toshiyasu Matsushima

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E100A ( 12 ) 2728 - 2731  2017.12

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • A Study on Analytical Properties of Bayesian Experimental Design Model based on an Orthonormal System

    Yoshifumi Ukita, Shunsuke Horii, Toshiyasu Matsushima

    Proceedings of Bayse on the Beach 2017     22 - 22  2017.11  [Refereed]

  • 復元および再生成の条件を一般化した再生成符号とその構成法

    鎌塚明, 東優太, 吉田隆弘, 松嶋敏泰

    電子情報学会論文誌 A   Vol.J100-A ( 11 ) 411 - 420  2017.11  [Refereed]

  • 2-レベル不均一誤り訂正符号の線形計画限界

    斎藤友彦, 新家稔央, 浮田善文, 松嶋敏泰, 平澤茂一

    電子情報学会論文誌 A   Vol.J100-A ( 9 ) 316 - 324  2017.09  [Refereed]

  • Variable-length lossy compression allowing positive overflow and excess distortion probabilities.

    Shota Saito, Hideki Yagi, Toshiyasu Matsushima

    2017 IEEE International Symposium on Information Theory(ISIT)   abs/1701.01800   1568 - 1572  2017.08

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • A note on asset management with sensor network

    Yasunari Maeda, Masakiyo Suzuki, Toshiyasu Matsushima

    IEEJ Transactions on Electronics, Information and Systems   137 ( 6 ) 817 - 818  2017

    　View Summary

    In this research we apply Markov decision processes to asset management with sensor network. We propose a new asset management method which minimizes total cost with reference to a Bayes criterion.

    DOI CiNii

    Scopus

    1
    Citation
    (Scopus)

  • A note on recommender system with transitions of user classes

    Yasunari Maeda, Masakiyo Suzuki, Toshiyasu Matsushima

    IEEJ Transactions on Electronics, Information and Systems   137 ( 6 ) 815 - 816  2017

    　View Summary

    In this research we apply Markov decision processes to recommender system with transitions of user classes. We propose a new recommender method which maximizes total reward with reference to a Bayes criterion.

    DOI CiNii

    Scopus

  • 半教師付き学習における一致性を満たすゆう度方程式の解に基づく予測の漸近評価

    安田豪毅, 宮希望, 須子統太, 松嶋敏泰

    電子情報通信学会論文誌A   Vol.J100-A ( 1 ) 102 - 113  2017.01

  • A note on asset management with sensor network

    Yasunari Maeda, Masakiyo Suzuki, Toshiyasu Matsushima

    IEEJ Transactions on Electronics, Information and Systems   137 ( 6 ) 817 - 818  2017  [Refereed]

    　View Summary

    In this research we apply Markov decision processes to asset management with sensor network. We propose a new asset management method which minimizes total cost with reference to a Bayes criterion.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • A note on recommender system with transitions of user classes

    Yasunari Maeda, Masakiyo Suzuki, Toshiyasu Matsushima

    IEEJ Transactions on Electronics, Information and Systems   137 ( 6 ) 815 - 816  2017  [Refereed]

    　View Summary

    In this research we apply Markov decision processes to recommender system with transitions of user classes. We propose a new recommender method which maximizes total reward with reference to a Bayes criterion.

    DOI

    Scopus

  • Threshold of Overflow Probability Using Smooth Max-Entropy in Lossless Fixed-to-Variable Length Source Coding for General Sources

    Shota Saito, Toshiyasu Matsushima

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E99A ( 12 ) 2286 - 2290  2016.12  [Refereed]

    DOI CiNii

    Scopus

    2
    Citation
    (Scopus)

  • Second-Order Achievable Rate Region of Slepian-Wolf Coding Problem in terms of Smooth Max-Entropy for General Sources

    Shota Saito, Toshiyasu Matsushima

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E99A ( 12 ) 2275 - 2280  2016.12  [Refereed]

    　View Summary

    This letter deals with the Slepian-Wolf coding problem for general sources. The second-order achievable rate region is derived using quantity which is related to the smooth max-entropy and the conditional smooth max-entropy. Moreover, we show the relationship of the functions which characterize the second-order achievable rate region in our study and previous study.

    DOI CiNii

    Scopus

  • Linear Programming Decoding of Binary Linear Codes for Symbol-Pair Read Channel

    Shunsuke Horii, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E99A ( 12 ) 2170 - 2178  2016.12  [Refereed]

    DOI CiNii

    Scopus

    7
    Citation
    (Scopus)

  • Threshold of overflow probability using smooth max-entropy in lossless fixed-to-variable length source coding for general sources

    Shota Saito, Toshiyasu Matsushima

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E99A ( 12 ) 2286 - 2290  2016.12

    　View Summary

    We treat lossless fixed-to-variable length source coding under general sources for finite block length setting. We evaluate the threshold of the overflow probability for prefix and non-prefix codes in terms of the smooth max-entropy. We clarify the difference of the thresholds between prefix and non-prefix codes for finite block length. Further, we discuss our results under the asymptotic block length setting.

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Second-order achievable rate region of Slepian-Wolf coding problem in terms of smooth max-entropy for general sources

    Saito, Shota, Matsushima, Toshiyasu

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E99A ( 12 ) 2275 - 2280  2016.12

    　View Summary

    Copyright © 2016 The Institute of Electronics, Information and Communication Engineers.This letter deals with the Slepian-Wolf coding problem for general sources. The second-order achievable rate region is derived using quantity which is related to the smooth max-entropy and the conditional smooth max-entropy. Moreover, we show the relationship of the functions which characterize the second-order achievable rate region in our study and previous study.

    DOI

    Scopus

  • Linear programming decoding of binary linear codes for symbol-pair read channel

    Horii, Shunsuke, Matsushima, Toshiyasu, Hirasawa, Shigeichi

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E99A ( 12 ) 2170 - 2178  2016.12

    　View Summary

    Copyright © 2016 The Institute of Electronics, Information and Communication Engineers.In this study, we develop a new algorithm for decoding binary linear codes for symbol-pair read channels. The symbol-pair read channel was recently introduced by Cassuto and Blaum to model channels with higher write resolutions than read resolutions. The proposed decoding algorithm is based on linear programming (LP). For LDPC codes, the proposed algorithm runs in time polynomial in the codeword length. It is proved that the proposed LP decoder has the maximum-likelihood (ML) certificate property, i.e., the output of the decoder is guaranteed to be the ML codeword when it is integral. We also introduce the fractional pair distance df p of the code, which is a lower bound on the minimum pair distance. It is proved that the proposed LP decoder corrects up to df p =2 - 1 errors.

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Linear programming decoding of binary linear codes for symbol-pair read channels.

    Shunsuke Horii, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE International Symposium on Information Theory(ISIT)   abs/1508.01640   1944 - 1948  2016  [Refereed]

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • Evaluation of overflow probability of Bayes code in moderate deviation regime.

    Shota Saito, Toshiyasu Matsushima

    2016 International Symposium on Information Theory and Its Applications(ISITA)     1 - 5  2016

  • Threshold of overflow probability in terms of smooth max-entropy for variable-length compression allowing errors.

    Shota Saito, Toshiyasu Matsushima

    2016 International Symposium on Information Theory and Its Applications(ISITA)     21 - 25  2016

  • Theoretical limit of type-I hybrid selective-repeat ARQ with finite receiver buffer.

    Yasunari Maeda, Toshiyasu Matsushima

    2016 International Symposium on Information Theory and Its Applications(ISITA)     582 - 585  2016  [Refereed]

  • A note on support recovery of sparse signals using linear programming.

    Shunsuke Horii, Toshiyasu Matsushima, Shigeichi Hirasawa

    2016 International Symposium on Information Theory and Its Applications(ISITA)     270 - 274  2016  [Refereed]

  • A maximum likelihood decoding algorithm of Gabidulin codes in deterministic network coding.

    Koki Kazama, Akira Kamatsuka, Toshiyasu Matsushima

    2016 International Symposium on Information Theory and Its Applications(ISITA)     666 - 670  2016  [Refereed]

  • Relationships between correlation of information stored on nodes and coding efficiency for cooperative regenerating codes.

    Takahiro Yoshida, Toshiyasu Matsushima

    2016 International Symposium on Information Theory and Its Applications(ISITA)     31 - 35  2016  [Refereed]

  • A note on unequal error protection in random network coding.

    Tomohiko Saito, Koki Kazama, Toshihiro Niinomi, Toshiyasu Matsushima

    2016 International Symposium on Information Theory and Its Applications(ISITA)   115 ( 394(IT2015 48-100) ) 661 - 665  2016  [Refereed]

    J-GLOBAL

  • Regenerating codes with generalized conditions of reconstruction and regeneration.

    Akira Kamatsuka, Yuta Azuma, Takahiro Yoshida, Toshiyasu Matsushima

    2016 International Symposium on Information Theory and Its Applications(ISITA)     41 - 45  2016  [Refereed]

  • Spatially "Mt. Fuji" coupled LDPC codes.

    Yuta Nakahara, Shota Saito, Toshiyasu Matsushima

    2016 International Symposium on Information Theory and Its Applications(ISITA)     201 - 205  2016

  • Evaluation of the Bayes Code from Viewpoints of the Distribution of Its Codeword Lengths

    Shota Saito, Nozomi Miya, Toshiyasu Matsushima

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E98A ( 12 ) 2407 - 2414  2015.12  [Refereed]

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • On the Credible Interval Prediction of Web Traffic based on the Bayes Decision Theory

    Daiki Koizumi, Toshiyasu Matsushima

    Proceeding of the 38th Symposium on Information Theory and its Applications (SITA2015)   38th   235 - 240  2015.11

    J-GLOBAL

  • On the Bayes Optimal Prediction of Time Series under a Nonstationary Weibull Distribution

    Daiki Koizumi, Toshiyasu Matsushima

    IEICE Technical Report (IT2015-33)   115 ( 137 ) 95 - 100  2015.07

    CiNii J-GLOBAL

  • Fundamental limit and pointwise asymptotics of the Bayes code for Markov sources.

    Shota Saito, Nozomi Miya, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)     1986 - 1990  2015

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • Evaluation of the Bayes Code from Viewpoints of the Distribution of Its Codeword Lengths

    SAITO Shota, MIYA Nozomi, MATSUSHIMA Toshiyasu

    IEICE Trans. Fundamentals   98 ( 12 ) 2407 - 2414  2015

    　View Summary

    This paper considers universal lossless variable-length source coding problem and investigates the Bayes code from viewpoints of the distribution of its codeword lengths. First, we show that the codeword lengths of the Bayes code satisfy the asymptotic normality. This study can be seen as the investigation on the asymptotic shape of the distribution of codeword lengths. Second, we show that the codeword lengths of the Bayes code satisfy the law of the iterated logarithm. This study can be seen as the investigation on the asymptotic end points of the distribution of codeword lengths. Moreover, the overflow probability, which represents the bottom of the distribution of codeword lengths, is studied for the Bayes code. We derive upper and lower bounds of the infimum of a threshold on the overflow probability under the condition that the overflow probability does not exceed ε∈(0,1). We also analyze the necessary and sufficient condition on a threshold for the overflow probability of the Bayes code to approach zero asymptotically.

    CiNii

  • Welcome message from the IECON2015 general chairs

    Kiyoshi Ohishi, Hideki Hashimoto, Toshiyuki Murakami, Leopoldo G. Franquelo, Mo-Yuen Chow

    IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society     1 - 2  2015

    DOI

  • Foreword: Special section on information theory and its applications

    Toshiyasu Matsushima, Manabu Kobayashi, Shiro Ikeda, Shogo Usami, Kenta Kasai, Shigeaki Kuzuoka, Hiroki Koga, Tetsuya Kojima, Masayuki Goto, Tatsumi Konishi, Hidetoshi Saito, Ryuichi Sakai, Mikihiko Nishiara, Ryo Nomura, Mitsuru Hamada, Masaya Fujisawa, Tetsunao Matsuta, Ryutaroh Matsumoto, Kazuhiko Minematsu, Kazushi Mimura, Hideki Yagi

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E97A ( 12 ) 2287  2014.12  [Refereed]

  • Asymptotics of Bayesian Inference for a Class of Probabilistic Models under Misspecification

    Nozomi Miya, Tota Suko, Goki Yasuda, Toshiyasu Matsushima

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E97A ( 12 ) 2352 - 2360  2014.12  [Refereed]

    DOI

    Scopus

  • A Note on Improvement in the Rate of a Prediction Error of AdaBoost in Pattern Recognition

    Hideyuki Masui, Ryoma Tsuzuki, Nozomi Miya, Toshiyasu Matsushima

    IPSJ SIG Notes. CVIM   2014 ( 1 ) 1 - 6  2014.08

    　View Summary

    AdaBoost is an algorithm used for pattern recognition. This algorithm successively makes the model which minimizes an error for sample data. However, to consider prediction, there is no guarantee that such model is optimum. Regarding this issue, there are many studies about regularization method and variable selection method. Forward selection method is one of the methods of variable selection method and Stagewise is one of the methods of forward selection method. Each iteration, Stagewise selects one variable. Stagewise updates parameters slightly increase and not minimizes an error for sample data. It is known that Stagewise improves the rate of a prediction error. In this research, we apply the idea of Stagewise for AdaBoost and consider improvement the rate of a prediction error.

    CiNii J-GLOBAL

  • Foreword.

    Toshiyasu Matsushima

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   97-A ( 12 ) 2287 - 2287  2014

    DOI

  • A note on the correlated multiple matrix completion based on the convex optimization method.

    Shunsuke Horii, Toshiyasu Matsushima, Shigeichi Hirasawa

    2014 IEEE International Conference on Systems, Man, and Cybernetics(SMC)     1618 - 1623  2014  [Refereed]

    DOI

  • Robustness of syndrome analysis method in highly structured fault-diagnosis systems.

    Manabu Kobayashi, Masayuki Goto, Toshiyasu Matsushima, Shigeichi Hirasawa

    2014 IEEE International Conference on Systems, Man, and Cybernetics(SMC)     2757 - 2763  2014

    DOI

  • Evaluation of the minimum overflow threshold of bayes codes for a Markov source.

    Shota Saito, Nozomi Miya, Toshiyasu Matsushima

    International Symposium on Information Theory and its Applications(ISITA)     211 - 215  2014

  • Privacy-preserving Distributed Calculation Methods of a Least-squares Estimator for Linear Regression Models

    SUKO Tota, HORII Shunsuke, KOBAYASHI Manabu, GOTO Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    J. Jpn . Ind. Manage. Assoc.   65 ( 2 ) 78 - 88  2014

    　View Summary

    In this paper, we study a privacy preserving linear regression analysis. We propose a new protocol of a distributed calculation method that calculates a least squares estimator, in the case that two parties have different types of explanatory variables. We show the security of privacy in the proposed protocol. Because the protocol have iterative calculations, we evaluate the number of iterations via numerical experiments. Finally, we show an extended protocol that is a distributed calculation method for k parties.

    DOI CiNii

  • The Empirical Bayes Forecasting of Web Traffic on the Non-Stationary Poisson Distribution

    Daiki Koizumi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceeding of the 36th Symposium on Information Theory and its Applications (SITA2013)   36th   432 - 436  2013.11

    J-GLOBAL

  • A Note on A Strategy for Role-Playing Game with Nonplayer Characters

    MAEDA Yasunari, GOTO Fumitaro, MASUI Hiroshi, MASUI Fumito, SUZUKI Masakiyo, MATSUSHIMA Toshiyasu

    The Transactions of the Institute of Electronics, Information and Communication Engineers. A   96 ( 8 ) 572 - 581  2013.08

    CiNii

  • Active Learning Strategy for Role-playing Game Modeled by Markov Decision Processes

    MAEDA Yasunari, GOTO Fumitaro, MASUI Hiroshi, MASUI Fumito, SUZUKI Masakiyo, MATSUSHIMA Toshiyasu

    Journal of Biomedical Fuzzy Systems Association   15 ( 1 ) 69 - 81  2013.06

    　View Summary

    In previous research a role-playing game(RPG) is represented with Markov decision processes(MDP). But active learning method for RPG has not been studied yet. In this research we propose an active learning method which maximizes an expected total reward with respect to a Bayes criterion under the condition that the true parameter of MDP is unknown. We recognize the effectiveness of our proposed method by some simulations.

    DOI CiNii

  • Iterative multiuser joint decoding based on ADMM.

    Shunsuke Horii, Tota Suko, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE Global Conference on Signal and Information Processing(GlobalSIP)     1097 - 1100  2013

    DOI

    Scopus

  • An Optimal Prediction Method Using Hierarchical N-gram Based on Bayesian Decision Theory

    Takashi Suenaga, Toshiyasu Matsushima

      vol.6 ( no.1 ) 102 - 110  2013  [Refereed]

    　View Summary

    Predictive word is an input technology showing candidate words which a system predict by user partial input. We treat predictive methods using an N-gram model. The model is generally produced by analyzing train data. The data is more sparse in proportion to an N-gram order, because of enormous combinations of words in the sequences. An issue of producing the model is how to combine a lower order model into a higher order one. Many researchers proposed models composed of weighed each-order one, such as a mixture distribution or an interpolation created by discount parameters considering about extremely lower frequent sequence. But these methods have no theoretical guarantee about prediction errors. In this paper, we treat the issue as a statistical problem that the model order is unknown, and discuss prediction errors from a point of view about Bayesian decision theory. We present that an optimal prediction method with reference to the Bayes criterion for minimizing the errors. Experimental results using Japanese documents show that our method performs good predictive words.

  • A study on the degrees of freedom in an experimental design model based on an orthonormal system

    Yoshifumi Ukita, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E96-A ( 2 ) 658 - 662  2013

    DOI

    Scopus

  • A Generalized Ramp Scheme for Key Distribution Scheme and an Optimal Construction

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    The Transactions of the Institute of Electronics, Information and Communication Engineers. A   95 ( 10 ) 723 - 736  2012.10

    CiNii

  • An error probability estimation of the document classification using Markov model.

    Manabu Kobayashi, Hiroshi Ninomiya, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the International Symposium on Information Theory and its Applications(ISITA)     717 - 721  2012  [Refereed]

  • A note on ANOVA in an experimental design model based on an orthonormal system.

    Yoshifumi Ukita, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics(SMC)     1990 - 1995  2012

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Fault diagnosis algorithm in multi-computer systems based on Lagrangian relaxation method.

    Shunsuke Horii, Manabu Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the International Symposium on Information Theory and its Applications(ISITA)     712 - 716  2012

  • Information spectrum approach to overflow probability of variable-length codes with conditional cost function.

    Ryo Nomura, Toshiyasu Matsushima

    Proceedings of the 2012 IEEE International Symposium on Information Theory(ISIT)   abs/1205.1242   1097 - 1101  2012

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Asymptotics of Bayesian estimation for nested models under misspecification.

    Nozomi Miya, Tota Suko, Goki Yasuda, Toshiyasu Matsushima

    Proceedings of the International Symposium on Information Theory and its Applications(ISITA)     86 - 90  2012

  • The optimal key estimation of stream ciphers and its approximation algorithm based on a probabilistic inference.

    Yuji Iikubo, Shunsuke Horii, Toshiyasu Matsushima

    Proceedings of the International Symposium on Information Theory and its Applications(ISITA)     531 - 535  2012

  • Variable Order Transition Probability Markov Decision Process for the Recommendation System

    Shuhei Kuwata, Yasunari Maeda, Toshiyasu Matsushima, Shigeichi Hirasawa

      vol.6 ( no.1 ) 20 - 30  2012  [Refereed]

    　View Summary

    In this paper, we propose a general markov decision process model for the recommendation system. Furthermore, by using historical data, we derive the optimal recommendation lists from the proposed model based on bayesian decision theory. In the recommendation research area, there were little studies that considered both the purchased items and the past recommended items within a given period. In these circumstances, markov decision process based recommend method that can take these two things into account has been proposed. Our method also uses both things as with the previous method. Here, the unique thing about this paper is not only that we generalize the existing model, but also that we formulate the process to get the recommendation lists as the statistical decision problem. As a result, we can obtain the most suitable recommendation lists with respect to the purpose of the recommendation for a wide variety of recommendation scene. By using artificial data, we show the experimental results that our method can obtain more rewards than the conventional method gets.

  • A Note on Relation between the Fourier Coefficients and the Effects in the Experimental Design

    Ukita, Yoshifumi, Matsushima, Toshiyasu

    Journal of Communication and Computer   vol.9 ( no.7 ) 830 - 836  2012  [Refereed]

    　View Summary

    It has recently been shown that the model in experimental design can be expressed in terms of an orthonormal system. In this case, the model is expressed by using Fourier coefficients instead of the effect of each factor. As there is an abundance of software for calculating the Fourier transform, such a system allows for a straightforward implementation of the procedures for estimating the Fourier coefficients by using Fourier transform. However, Fourier coefficients themselves do not provide a direct representation of the effect of each factor, and the relation between the Fourier coefficients and the effect of each factor has not yet been clarified. In this paper, we present theorems of the relation between the Fourier coefficients and the effect of each factor. By using these theorems, the effect of each factor can be easily obtained from the computed Fourier coefficients. Therefore, with the aid of an orthonormal system, it is possible to easily implement the estimation procedures as well as to understand how each factor affects the response variable in the model.

  • Berkeley Report

    MATSUSHIMA Toshiyasu

    IEICE Fundamentals Review   5 ( 3 ) 281 - 282  2012

    CiNii

  • An Analysis of Slepian-Wolf Coding Problem Based on the Asymptotic Normality

    Ryo Nomura, Toshiyasu Matsushima

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E94A ( 11 ) 2220 - 2225  2011.11  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • On the Overflow Probability of Fixed-to-Variable Length Codes with Side Information

    Ryo Nomura, Toshiyasu Matsushima

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E94A ( 11 ) 2083 - 2091  2011.11  [Refereed]

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • A Note on the Linear Programming Decoding of Binary Linear Codes for Multiple-Access Channel

    Shunsuke Horii, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E94A ( 6 ) 1230 - 1237  2011.06  [Refereed]

    　View Summary

    In this paper, we develop linear-programming (LP) decoding for multiple-access channels with binary linear codes. For single-user channels, LP decoding has attracted much attention in recent years as a good approximation to maximum-likelihood (ML) decoding. We demonstrate how the ML decoding problem for multiple-access channels with binary linear codes can be formulated as an LP problem. This is not straightforward, because the objective function of the problem is generally a non-linear function of the codeword symbols. We introduce auxiliary variables such that the objective function is a linear function of these variables. The ML decoding problem then reduces to the LP problem. As in the case for single-user channels, we formulate the relaxed LP problem to reduce the complexity for practical implementation, and as a result propose a decoder that has the desirable property known as the ML certificate property (i.e., if the decoder outputs an integer solution, the solution is guaranteed to be the ML codeword). Although the computational complexity of the proposed algorithm is exponential in the number of users, we can reduce this complexity for Gaussian multiple-access channels. Furthermore, we compare the performance of the proposed decoder with a decoder based on the sum-product algorithm.

    DOI

    Scopus

  • Disk allocation methods for Cartesian product files using unequal error protection codes.

    Tomohiko Saito, Hiroshige Inazumi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics(SMC)     2437 - 2442  2011  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Probabilistic fault diagnosis and its analysis in multicomputer systems.

    Manabu Kobayashi, Toshinori Takabatake, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics(SMC)   E101-A ( 12 ) 1205 - 1211  2011

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • A note on the degrees of freedom in an experimental design model based on an orthonormal system.

    Yoshifumi Ukita, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics(SMC)     2181 - 2185  2011

    DOI

    Scopus

  • A Note on Relation between the Fourier Coefficients and the Effects in the Experimental Design

    Yoshifumi Ukita, Toshiyasu Matsushima

    8th International Conference on Information(ICICS)     1 - 5  2011

    DOI

    Scopus

  • System evaluation of disk allocation methods for Cartesian product files by using error correcting codes.

    Shigeichi Hirasawa, Tomohiko Saito, Hiroshige Inazumi, Toshiyasu Matsushima

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics(SMC)     2443 - 2448  2011

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • A Description of Experimental Design on the Basis of an Orthonormal System

    Yoshifumi Ukita, Toshiyasu Matsushima

    Applications of Digital Signal Processing, Edited by Christian Cuadrado-Laborde, InTech Publisher     365 - 378  2011

    　View Summary

    In this chapter, we propose that the model of experimental design be expressed as an orthonormal system, and show that the model contains no redundant parameters. Then, the model is expressed by using Fourier coefficients instead of the effect of each factor. As there is an abundance of software for calculating the Fourier transform, such a system allows for a straightforward implementation of the procedures for estimating the Fourier coefficients by using Fourier transform. In addition, the effect of each factor can be easily obtained from the Fourier coefficients. Therefore, it is possible to implement easily the estimation procedures as well as to understand how each factor affects the response variable in a model based on an orthonormal system. Moreover, the analysis of variance can also be performed in a model based on an orthonormal system. Hence, it is clear that two main procedures in the experimental design, that is, the estimation of the effects and the analysis of variance can be executed in a description of experimental design on the basis of an orthonormal system.

    DOI

  • 私たちの仕事と家庭のバランス

    松嶋 敏泰, 松嶋 智子

    電子情報通信学会 通信ソサイエティマガジン   2011 ( 16 ) 16_16 - 16_17  2011

    DOI CiNii

  • A note on the linear programming decoding of binary linear codes for multiple-access channel

    Shunsuke Horii, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E94-A ( 6 ) 1230 - 1237  2011

    DOI

    Scopus

  • A note on document classification with small training data

    Yasunari Maeda, Hideki Yoshida, Masakiyo Suzuki, Toshiyasu Matsushima

    IEEJ Transactions on Electronics, Information and Systems   131 ( 8 ) 1459 - 1466  2011

    　View Summary

    Document classification is one of important topics in the field of NLP (Natural Language Processing). In the previous research a document classification method has been proposed which minimizes an error rate with reference to a Bayes criterion. But when the number of documents in training data is small, the accuracy of the previous method is low. So in this research we use estimating data in order to estimate prior distributions. When the training data is small the accuracy using estimating data is higher than the accuracy of the previous method. But when the training data is big the accuracy using estimating data is lower than the accuracy of the previous method. So in this research we also propose another technique whose accuracy is higher than the accuracy of the previous method when the training data is small, and is almost the same as the accuracy of the previous method when the training data is big. © 2011 The Institute of Electrical Engineers of Japan.

    DOI CiNii

    Scopus

  • A Note on the Branch-and-Cut Approach to Decoding Linear Block Codes

    Shunsuke Horii, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E93A ( 11 ) 1912 - 1917  2010.11  [Refereed]

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Estimation of the Effects in the Experimental Design Using Fourier Transforms

    Yoshifumi Ukita, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E93A ( 11 ) 2077 - 2082  2010.11  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • A Note on the Branch-and-Cut Approach to Decoding Linear Block Codes

    堀井俊佑, 松嶋敏泰, 平澤茂一

    IEICE Trans. Fundamentals   Vol.E93-A ( No.11 ) 1912 - 1917  2010.11

  • Applying Makov Decision Processes to Selective-Repeat ARQ with Finite Operation Time and Finite Receiver Buffer

    MAEDA Yasunari, AMEMIYA Koji, KOBAYASHI Naoto, YOSHIDA Hideki, SUZUKI Masakiyo, MATSUSHIMA Toshiyasu

    The Transactions of the Institute of Electronics, Information and Communication Engineers. A   93 ( 8 ) 572 - 578  2010.08

    CiNii

  • A Note on a Sampling Theorem for Functions over GF(q)(n) Domain

    Yoshifumi Ukita, Tomohiko Saito, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E93A ( 6 ) 1024 - 1031  2010.06  [Refereed]

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • Optimal Ramp Scheme for Key Predistribution System with Multiple Key Distribution Centers

    YOSHIDA Takahiro, MATSUSHIMA Toshiyasu, IMAI Hideki

    The Transactions of the Institute of Electronics, Information and Communication Engineers. A   93 ( 4 ) 277 - 288  2010.04

    CiNii

  • On the Web Traffic Modeling under the Opening and Closing Services by the Non-Stationary Poisson Process

    Daiki Koizumi, Shunsuke Horii, Toshiyasu Matsushima

    IEICE Technical Report   109 ( 449 ) 343 - 347  2010.03

    J-GLOBAL

  • Toward computing the capacity region of degraded broadcast channel.

    Kensuke Yasui, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)     570 - 574  2010

    DOI

    Scopus

    8
    Citation
    (Scopus)

  • An accurate density evolution analysis for a finite-state Markov channel

    Naoto Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Journal of Discrete Mathematical Sciences and Cryptography   13 ( 1 ) 85 - 97  2010

    　View Summary

    In this paper, we consider density evolution analyses of low-density parity-check (LDPC) codes for a finite-state Markov channel (FSMC). Since operations in the subgraph corresponding to the estimation process do not satisfy symmetry conditions, all densities involved in each value of the channel state should be kept track. In [6], to avoid the complexity to compute plural pdfs, only one pdf involved in the channel state is computed exploiting marginalization operations. We suppose that this approach is not accurate enough to track the estimation process of the joint estimation-decoding. In this paper, we present a procedure of the density evolution analysis of LDPC codes for an FSMC of which all densities involved in each value of the channel state are kept track. © 2010 Taylor &amp
    Francis Group, LLC.

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • A Linear Programming Bound for Unequal Error Protection Codes

    Tomohiko Saito, Yoshifumi Ukita, Toshiyasu Matsushima, Shigeichi Hirasawa

    2010 AUSTRALIAN COMMUNICATIONS THEORY WORKSHOP     24 - +  2010

    　View Summary

    In coding theory, it is important to calculate an upper bound for the size of codes given the length and minimum distance. The Linear Programming (LP) bound is known as a good upper bound for the size of codes. On the other hand, Unequal Error Protection (UEP) codes have been studied in coding theory. In UEP codes, a codeword has special bits which are protected against a greater number of errors than other bits. In this paper, we propose a LP bound for UEP codes. Firstly, we generalize the distance distribution (or weight distribution) of codes. Under the generalization, we lead to the LP bound for UEP codes. And we show a numerical example of the LP bound for UEP codes. Lastly, we compare the proposed bound with a modified Hamming bound.

  • On the Overflow Probability of Fixed-to-Variable Length Codes with Side Information

    Ryo Nomura, Toshiyasu Matsushima

    2010 DATA COMPRESSION CONFERENCE (DCC 2010)     548 - 548  2010

    DOI

    Scopus

  • On the overflow probability of lossless codes with side information.

    Ryo Nomura, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)     131 - 135  2010

    DOI

    Scopus

  • On the Appropriate Organizational Size for Each Research Community

    MATSUSHIMA Toshiyasu

    IEICE Fundamentals Review   4 ( 1 ) 2 - 4  2010

    CiNii

  • KL情報量を制約としたResolvability問題における達成可能条件の評価

    野村亮, 吉田隆弘, 松嶋敏泰

    電子情報通信学会論文誌   Vol. J93-A ( No.3 ) 216 - 221  2010

  • 多端子情報理論に基づくセンサネットワークのモデル化と信頼度評価

    野村亮, 松嶋敏泰

    情報処理学会論文誌:数理モデル化と応用   Vol3 ( No.1 ) 13 - 24  2010

    J-GLOBAL

  • 複数の鍵配送センターを用いたランプ型鍵事前配布方式

    吉田隆弘, 松嶋敏泰, 今井秀樹

    電子情報通信学会論文誌A   Vol.J93-A ( No.4 ) 277 - 288  2010

  • A note on a sampling theorem for functions over GF(q)n domain

    Yoshifumi Ukita, Tomohiko Saito, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E93-A ( 6 ) 1024 - 1031  2010

    　View Summary

    In digital signal processing, the sampling theorem states that any real valued function f can be reconstructed from a sequence of values of f that are discretely sampled with a frequency at least twice as high as the maximum frequency of the spectrum of f . This theorem can also be applied to functions over finite domain. Then, the range of frequencies of f can be expressed in more detail by using a bounded set instead of the maximum frequency. A function whose range of frequencies is confined to a bounded set is referred to as bandlimited function. And a sampling theorem for bandlimited functions over Boolean domain has been obtained. Here, it is important to obtain a sampling theorem for bandlimited functions not only over Boolean domain (GF(2) n domain) but also over GF(q)n domain, where q is a prime power and GF(q) is Galois field of order q. For example, in experimental designs, although the model can be expressed as a linear combination of the Fourier basis functions and the levels of each factor can be represented by GF(q), the number of levels often take a value greater than two. However, the sampling theorem for bandlimited functions over GF(q)n domain has not been obtained. On the other hand, the sampling points are closely related to the codewords of a linear code. However, the relation between the parity check matrix of a linear code and any distinct error vectors has not been obtained, although it is necessary for understanding the meaning of the sampling theorem for bandlimited functions. In this paper, we generalize the sampling theorem for bandlimited functions over Boolean domain to a sampling theorem for bandlimited functions over GF(q)n domain. We also present a theorem for the relation between the parity check matrix of a linear code and any distinct error vectors. Lastly, we clarify the relation between the sampling theorem for functions over GF(q)n domain and linear codes. © 2010 The Institute of Electronics, Information and Communication Engineers.

    DOI

    Scopus

    6
    Citation
    (Scopus)

  • マルコフ決定過程の動作時間と受信バッファ容量が有限の選択再送ARQへの適用

    前田康成, 雨宮康二, 小林直人, 吉田秀樹, 鈴木正清, 松嶋敏泰

    電子情報通信学会論文誌A   Vol.J93-A ( No.8 ) 572 - 578  2010

    CiNii

  • A note on automatic construction algorithms for orthogonal designs of experiments using error-correcting codes

    Tomohiko Saito, Toshiyasu Matsushima, Shigeichi Hirasawa

    Journal of Discrete Mathematical Sciences and Cryptography   13 ( 4 ) 369 - 381  2010

    　View Summary

    In the field of experimental design, it is important to construct orthogonal designs. In this paper, we propose a new algorithm to construct orthogonal design. This algorithm uses Ukita’s algorithm, which is essentially based on projective geometries, and uses orthogonal designs constructed by error-correcting codes. We show some numerical examples of the proposed algorithm, and show that the proposed algorithm can construct good orthogonal designs with low complexity even if there are high order effects. © 2010 Taylor &amp
    Francis Group, LLC.

    DOI

    Scopus

  • Asymptotic property of universal lossless coding for independent piecewise identically distributed sources

    Tota Suko, Toshiyasu Matsushima, Shigeichi Hirasawa

    Journal of Discrete Mathematical Sciences and Cryptography   13 ( 4 ) 383 - 391  2010

    　View Summary

    The universal lossless source coding problem is one of the most important problem in communication systems. The aim of source coding is to compress data to reduce costs in digital communication. Traditional universal source coding schemes are usually designed for stationary sources. Recently, some universal codes for nonstationary sources have been proposed. Independent piecewise identically distributed (i.p.i.d.) sources are simple nonstationary sources that parameter changes discontinuously. In this paper, we assume new i.p.i.d. sources class, and we prove that Bayes codes minimize the mean redundancy when parameter transition pattern is known and parameter is unknown. © 2010 Taylor &amp
    Francis Group, LLC.

    DOI

    Scopus

  • On the Condition of epsilon-Transmissible Joint Source-Channel Coding for General Sources and General Channels

    Ryo Nomura, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E92A ( 11 ) 2936 - 2940  2009.11  [Refereed]

    DOI

    Scopus

  • Generalization and Extension of XEX* Mode

    Kazuhiko Minematsu, Toshiyasu Matsushima

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E92A ( 2 ) 517 - 524  2009.02  [Refereed]

    DOI

    Scopus

    8
    Citation
    (Scopus)

  • Document classification method with small training data

    Yasunari Maeda, Hideki Yoshida, Toshiyasu Matsushima

    ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings     138 - 141  2009

    　View Summary

    Document classification is one of important topics in the field of NLP(Natural Language Processing). In our previous research we've proposed a document classification method which minimizes an error rate with reference to a Bayes criterion. But when the number of documents in training data is small, the accuracy of the previous method is low. So in this research we propose a document classification method whose accuracy is higher than the previous method when the number of documents in training data is small. © 2009 SICE.

  • Fingerprinting Codes for Multimedia Data against Averaging Attack

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E92A ( 1 ) 207 - 216  2009.01  [Refereed]

    DOI

    Scopus

  • Bayesian Forecasting of WWW Traffic on the Time Varying Poisson Model

    Daiki Koizumi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications(PDPTA)   abs/0906.3923   683 - 689  2009

  • Reducing the space complexity of a Bayes coding algorithm using an expanded context tree.

    Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE International Symposium on Information Theory(ISIT)     719 - 723  2009

    DOI

    Scopus

    22
    Citation
    (Scopus)

  • A Note on the Relation between a Sampling Theorem for Functions over a GF (q)n Domain and Linear Codes.

    Yoshifumi Ukita, Tomohiko Saito, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics(SMC)     2665 - 2670  2009

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • On Precise Achievable Conditions in Resolvability Problem Based on the Asymptotic Normality

    野村亮, 松嶋敏泰

    Far East Journal of Electronics and Communications   Vol.3 ( No.3 ) 85 - 99  2009

  • Density Evolution Analysis of Robustness for LDPC Codes over the Gilbert-Elliott Channel

    Manabu Kobayashi, Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E91A ( 10 ) 2754 - 2764  2008.10  [Refereed]

    DOI

    Scopus

  • A Combined Matrix Ensemble of Low-Density Parity-Check Codes for Correcting a Solid Burst Erasure

    Gou Hosoya, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E91A ( 10 ) 2765 - 2778  2008.10  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Error control codes for parallel channel with correlated errors.

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    2008 IEEE Information Theory Workshop(ITW)     421 - 425  2008  [Refereed]

    DOI

    Scopus

  • An Efficient Design of Irregular LDPC Codes using Beta Approximation for the Gilbert-Elliott Channel

    Manabu Kobayashi, Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    2008 INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY AND ITS APPLICATIONS, VOLS 1-3     1543 - +  2008  [Refereed]

    　View Summary

    In this paper, we investigate the design of low-density parity-check (LDPC) codes for the Gilbert-Elliott (GE) channel. Recently, Eckford et al. proposed a design method of irregular LDPC codes using approximate density-evolution (DE) for Markov channels [7]. In the design method proposed by Eckford et al., the probability density function (PDF) of the messages from variable nodes to check nodes is approximated by the Gaussian distribution. In this paper, we first show the method to obtain the accurate PDF of the messages from variable nodes to check nodes by utilizing two DE steps for the Gaussian distribution. We call this method the iterative density approximation (IDA). Using this method, we can design the good LDPC codes. Next, we propose an efficient design method of irregular LDPC codes by using Beta approximation to the PDF of the channel state probability for the GE channel. Consequently, we show that the complexity to calculate PDFs of the channel messages is considerably reduced though the rates of LDPC codes obtained by using the proposed approximation are almost the same as that of the IDA method.

  • A Ramp Scheme for Key Predistribution System against Collusion of Users and Centers

    Takahiro Yoshida, Toshiyasu Matsushima, Hideki Imai

    2008 INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY AND ITS APPLICATIONS, VOLS 1-3     531 - +  2008

    　View Summary

    In this paper, we consider a, ramp scheme for Key Pre-distribution System (KPS). In the ramp scheme, it can be regarded ass one kind of generalization of KPS, and the required resources can be reduced at the cost of a security degradation which depends on the size of users. We define a ramp scheme for KPS, show lower bound on the amount of user's information needed to generate a common key, and design a protocol that realize a ramp scheme for KPS.

  • On the Condition of epsilon-Transmissibility in Joint Source-Channel Coding for Mixed Sources and Mixed Channels

    Ryo Nomura, Toshiyasu Matsushima, Shigeichi Hirasawa

    2008 INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY AND ITS APPLICATIONS, VOLS 1-3     1299 - +  2008

    　View Summary

    In this study, we consider a joint source-channel coding problem. The joint source-channel coding theorem reveals the existence of a code for the pair of the source V and the channel W under the condition that the probability of error is smaller than or equal to E asymptotically. We show the separation theorem for general sources and general channels.

  • 拡張された有本-Blahutアルゴリズムの大域的収束性について

    安井謙介, 須子統太, 松嶋敏泰

    電子情報通信学会論文誌   Vol.91-A ( No.9 ) 846 - 860  2008

    CiNii

  • 外れ値データの発生を含む回帰モデルに対するベイズ予測アルゴリズム

    須子統太, 松嶋敏泰, 平澤茂一

    情報処理学会論文誌数理モデル化と応用   Vol.1 ( No.1 ) 17 - 26  2008

    CiNii

  • Improved MACs from differentially-uniform permutations

    Kazuhiko Minematsu, Toshiyasu Matsushima

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E90A ( 12 ) 2908 - 2915  2007.12  [Refereed]

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • Reliability-based hybrid ARQ scheme with encoded parity bit retransmissions and message passing decoding

    Daiki Koizumi, Naoto Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E90A ( 9 ) 1736 - 1744  2007.09  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • Short concatenated fingerprinting codes for multimedia data

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    45th Annual Allerton Conference on Communication, Control, and Computing 2007   2   1040 - 1045  2007

    　View Summary

    Digital fingerprinting , a copyright protection tech-nique of multimedia data , is considered. For digital finger-printing , measures against collusion attacks , where several fingerprinted copies of the same content are mixed to disturb their fingerprints , should be taken. In this paper , we propose a shortening method of collusion-secure fingerprinting codes based on finite geometries , which reduces the code length with keeping the number of codewords and the codes' resilience. We also propose a concatenated coding method which combines a conventional collusion-secure fingerprinting code and an error correcting code for increasing the coding rate , ue to the new fingerprinting codes , the system can deal with a larger number of users to distribute a digital content.

  • New bounds for PMAC, TMAC, and XCBC

    Kazuhiko Minematsu, Toshiyasu Matsushima

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   4593   434 - 451  2007

    DOI

    Scopus

    25
    Citation
    (Scopus)

  • Improved collusion-secure codes for digital fingerprinting based on finite geometries.

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics(SMC)     948 - 953  2007  [Refereed]

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Word segmentation for the sequences emitted from a word-valued source

    Takashi Ishida, Toshiyasu Matsushima, Shigeichi Hirasawa

    2007 CIT: 7TH IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY, PROCEEDINGS     662 - 667  2007  [Refereed]

    DOI

  • A note on morphological analysis methods based on statistical decision theory

    Yasunari Maeda, Naoya Ikeda, Hideki Yoshida, Yoshitaka Fujiwara, Toshiyasu Matsushima

    PROCEEDINGS OF SICE ANNUAL CONFERENCE, VOLS 1-8     1558 - +  2007  [Refereed]

    　View Summary

    Morphological analysis is one of important topics in the field of NLP(Natural Language Processing). In many previous research a HMM(Hidden Markov Model) with unknown parameters has been used as a language model. In this research we also use the HMM as the language model. And we assume that sate transitions in the HMM are dominated by a second order Markov chain. At first we propose two types of morphological analysis methods which minimize the error rate with reference to a Bayes criterion. But the computational complexity of the proposed Bayes optimal morphological analysis methods are exponential order. So we also propose approximate methods.

  • Text Data Compression by Bayes Coding Algorithm

    Akira Nakano, Daiki Koizumi, Toshiyasu Matsushima

    IPSJ SIG Notes   2007-AL-110 ( 5 ) 15 - 20  2007.01

    J-GLOBAL

  • Tweakable enciphering schemes from hash-sum-expansion

    Kazuhiko Minematsu, Toshiyasu Matsushima

    PROGRESS IN CRYPTOLOGY - INDOCRYPT 2007   4859   252 - 267  2007

    DOI

    Scopus

    18
    Citation
    (Scopus)

  • A class of prior distributions on context tree models and an efficient algorithm of the Bayes codes assuming it

    Toshiyasu Matsushima, Shigeicb Hirasawa

    2007 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY, VOLS 1-3     305 - +  2007

    　View Summary

    The CTW(Context Tree Weighting) algorithm is an efficient universal coding algorithm on context tree models. The CTW algorithm has been interpreted as the non-predictive Bayes coding algorithm assuming a special prior distribution over context tree models. An efficient recursive calculation method using a gathering context tree in the CTW algorithm is well known. Although there exist efficient recursive algorithms for the Bayes codes assuming a special class of prior distributions, the basic property of the prior distribution class has been scarcely investigated. In this paper we show the exact definition of a prior distribution class on context tree models that has the similar property to the class of conjugate priors. We show the posterior distribution is also included in the same distribution class as the prior distribution class. So we can also construct an efficient algorithm of predictive Bayes codes on context tree models by using the prior distribution class. Lastly the asymptotic mean code length of the codes is investigated.

  • A Note on Error Correction Schemes using LDPC codes with a High-Capacity Feedback Channel.

    Naoto Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE International Symposium on Information Theory(ISIT)     2381 - 2385  2007

    DOI

    Scopus

  • An Algorithm for Computing the Secrecy Capacity of Broadcast Channels with Confidential Messages.

    Kensuke Yasui, Tota Suko, Toshiyasu Matsushima

    IEEE International Symposium on Information Theory(ISIT)     936 - 940  2007

    DOI

    Scopus

    20
    Citation
    (Scopus)

  • On the -overflow probability of lossless codes.

    Ryo Nomura, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE International Symposium on Information Theory(ISIT)     441 - 445  2007

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • ストリーム暗号における擬似乱数生成器の構成に関する一考察

    三上暢仁, 齋藤友彦, 松嶋敏泰

    電子情報通信学会論文誌A   Vol.J90-A ( No.5 ) 470 - 476  2007

  • 無ひずみ情報源符号化におけるオーバフロー確率について

    野村亮, 松嶋敏泰, 平澤茂一

    電子情報通信学会論文誌   Vol.J90-A ( No.4 ) 292 - 304  2007

  • A note on the ∈-overflow probability of lossless codes

    Ryo Nomura, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E90-A ( 12 ) 2965 - 2970  2007

    DOI

    Scopus

    10
    Citation
    (Scopus)

  • Properties of a word-valued source with a non-prefix-free word set

    Takashi Ishida, Masayuki Goto, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E89A ( 12 ) 3710 - 3723  2006.12  [Refereed]

    DOI

    Scopus

    3
    Citation
    (Scopus)

  • A note on error correction schemes with a feedback channel

    Naoto Kobayashi, Daiki Koizumi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E89A ( 10 ) 2475 - 2480  2006.10  [Refereed]

    DOI

    Scopus

    2
    Citation
    (Scopus)

  • A Study of Bayes Coding for i.i.d. Sources with Consideration of the Generating Patterns of the Symbols in the Source Alphabet

    Ryunosuke Nanmo, Daiki Koizumi, Toshiyasu Matsushima

    IEICE Technical Report   106 ( 184 ) 25 - 30  2006.07

    J-GLOBAL

  • The Reliability based Hybrid ARQ Scheme with both the Encoded Parity Bit Retransmissions and Message Passing Decoding

    Daiki Koizumi, Naoto Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Technical Report of IEICE (IT2006-17)   106 ( 60 ) 23 - 28  2006.05

    　View Summary

    Reliability Based Hybrid ARQ (RB-HARQ) is an ARQ scheme using the modified feedback. In the RB-HARQ, the receiver returns both NAK signal and unreliable bit indices if the received sequence is not acknowledged. Since the unreliable bit index is determined by the bitwise posterior probability, better approximation of that probability is crucial. Assuming the systematic codes, the proposed RB-HARQ scheme has two features for this approximation: (1) The sender retransmits newly encoded parity bits corresponding to the unreliable information bits; (2) The retransmitted parity bits as well as the initial received sequence are put all together to perform the message passing decoding.

    CiNii

  • A note on construction of orthogonal arrays with unequal strength from error-correcting codes

    Tomohiko Saito, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E89A ( 5 ) 1307 - 1315  2006.05  [Refereed]

    DOI

    Scopus

    5
    Citation
    (Scopus)

  • Transformation of a parity-check matrix for a message-passing algorithm over the BEC

    Naoto Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E89A ( 5 ) 1299 - 1306  2006.05  [Refereed]

    DOI

    Scopus

    4
    Citation
    (Scopus)

  • Adaptive incremental redundancy coding and decoding schemes using feedback information

    Toshiyasu Matsushima

    Proceedings of 2006 IEEE Information Theory Workshop     189 - 193  2006

    　View Summary

    If we can use a high capacity feedback channel, the receiver may transmit the indices of unreliable bits in a received sequence instead of ACK/NAK signals. We consider the error correction schemes using the indices of unreliable bits. The suitable parity symbols are incrementally transmitted using the feedback information. The bitwise reliability can be calculated by message passing algorithms on the variable graph constructed by adding the new nodes and arcs corresponding to the received parity bits to a former graph at each stage.

  • On the Interleaver Design Method for Block Turbo Codes and Its Minimum Distance

    Manabu Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

      vol.J89-A ( no.2 ) 129 - 143  2006  [Refereed]

  • On Improvement of Error Exponents for Decision Feedback Scheme with LR+Th

    Toshihiro Niinomi, Toshiyasu Matsushima, Shigeichi Hirasawa

      vol.J89-A ( no.12 ) 1168 - 1174  2006  [Refereed]

  • ストリーム暗号への攻撃法の改良に関する一考察-多次元の相関を利用した攻撃-

    細渕智史, 斉藤友彦, 松嶋敏泰

    電子情報通信学会論文誌   Vol.J89-A ( No.2 ) 121 - 128  2006

  • A Note on HTTP Traffic Analysis of the Time Series Model with a Time Varying Density Parameter

    Daiki Koizumi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proc. of the 28th Symposium on Information Theory and Its Applications (SITA2005)   2   729 - 732  2005.12

  • 単一ループをもつグラフィカルモデルにおける確率伝播型アルゴリズムに関する一考察

    岡野 洋平, 小泉 大城, 松嶋 敏泰

    第28回情報理論とその応用学会(SITA2005)予稿集   1 ( Vol.1 ) 1 - 4  2005.12

    J-GLOBAL

  • A heuristic search method with the reduced list of test error patterns for maximum likelihood decoding

    H Yagi, T Matsushima, S Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E88A ( 10 ) 2721 - 2733  2005.10  [Refereed]

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • A Study of Reliability Based Hybrid ARQ Schemes Using a Recursive Systematic Convolutional Code

    Naoto Kobayashi, Daiki Koizumi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE technical report. Information theory   105 ( 311 ) 7 - 11  2005.09

    　View Summary

    The Reliability Based Hybrid ARQ (RBH-ARQ) is one of hybrid ARQ schemes. In the RBH-ARQ, the modified feedback is composed of both ACK/NAK signal and unreliable bit indices which is evaluted from bitwise posterior probabilities. Using the modified feedback information, a sender encodes and retransmits the codeword. In this paper, we propose several error correction procedures with the RBH-ARQ schemes based on a systematic convolutional code. These have differences in their use of received retransmitted informations. To evalute and compare the peformances of these algorithms, we consider use of received retransmitted informations and a constitution of the encoder in the RBH-ARQ schemes.

    CiNii J-GLOBAL

  • インターネットトラヒックのポアソン分布に従う非定常な時系列モデルを用いた解析に関する一考察

    小泉 大城, 松嶋 敏泰, 平澤 茂一

    第4回情報科学技術フォーラム(FIT2005)講演論文集   4   35 - 38  2005.08

  • A Study of Reliability Based Hybrid ARQ Scheme with Bitwise Posterior Probability Evaluation from Message Passing Algorithm

    Daiki Koizumi, Naoto Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Technical Report of IEICE (IT2005-24)   105 ( 85 ) 11 - 16  2005.05

  • Matrix Clustering Method Achieving Specific Accuracy by Modified Apriori Algorithm

    Kobayashi Manabu, Matsushima Toshiyasu, Hirasawa Shigeichi

    Abstracts of Annual Conference of Japan Society for Management Information   2005   4 - 4  2005

    　View Summary

    Matrix clustering is defined as a method to obtain submatrices with specified area and density ( the ratio of 1 element about submatrix ) for the given sparse binary matrix.This method has been proposed as a data mining technique for Customer Relationship Management(CRM) and makes it possible to cluster the related items and customers.In this paper, we extend the apriori algorithm and propose a new matrix clustering algorithm which obtains all submatrices satisfying some specific condition.As a result, it is possible to analyze the purchase information of the customers in detail.

    DOI CiNii J-GLOBAL

  • Bayes universal coding algorithm for side information context tree models.

    Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the 2005 IEEE International Symposium on Information Theory(ISIT)     2345 - 2348  2005

    DOI

    Scopus

  • A note on a decoding algorithm of codes on graphs with small loops.

    Naoto Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the IEEE ITSOC Information Theory Workshop 2005 on Coding and Complexity(ITW)     108 - 112  2005

    DOI

    Scopus

    1
    Citation
    (Scopus)

  • On Error Exponents for Variable Size List Decoder Using the Viterbi Algorithm with Likelihood Ratio Testing

    Toshihiro Niinomi, Toshiyasu Matsushima, Shigeichi Hirasawa

    The IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (Japanese edition) A   vol.J88-A ( no.11 ) 1343 - 1351  2005  [Refereed]

    CiNii

  • A Classification of the Probabilistic Reasoning given Distribution Evidence and Kullback-Leibler Information

    Toshiyasu Matsushima

    RIMS Kokyuroku   1420   163 - 173  2005

    　View Summary

    The probabilistic reasoning given distribution evidence, virtual evidence, indirect evidence or likelihood have been investigated in previous research.In this paper, we classify the reasoning into two types and define each type of the reasoning by mathematical formulas. We clarify the difference between two types by the definition. From the definition, we show that the first type of reasoning is solved by the minimization of Kullback-Leibler(K-L) information under marginal constraints and the second type is calculated by the ordinary probabilistic reasoning methods such as Belief Propagation(BP). We also show that the Iterative Scaling Procedure(ISP) is applied to the first type reasoning. Moreover, we propose an efficient propagation algorithm, which are based on ISP, for the reasoning on Junction trees. Both the space and the time complexities of the proposed algorithm are lower than that of the previous research

    CiNii

  • ターボ符号・LDPC符号とその復号法の概要

    松嶋敏泰

    電子情報通信学会誌   Vol.88 ( No.4 ) 244 - 248  2005

    CiNii

  • A Note on the Prediction Algorithm when Orthogonal Design is used for Query Learning

    浮田善文, 小泉大城行, 松嶋敏泰, 平沢茂一

    人工知能学会人工知能基本問題研究会資料   57th   25 - 32  2004.11

    J-GLOBAL

  • Efficient Reliability-based Soft Decision Decoding Algorithm over Markov Modulated Channel

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Trans. Fundamentals     823 - 828  2004.08

    CiNii

  • An Improvement Method of Reliability-Based Maximum Likelihood Decoding Algorithms Using an Order Relation among Binary Vectors

    Hideki Yagi, Nanabu Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Trans. Fundamentals     2493 - 2502  2004.08

  • A Study of Decoding Algorithm of Tailbiting Convolutional Codes

    岡野洋平, 小泉大城, 松嶋敏泰

    電子情報通信学会技術研究報告   104 ( 229 ) 47 - 52  2004.07

    J-GLOBAL

  • A New Decoding Algorithm Using Likelihood Ratio Testing for Tree Codes

    Toshihiro Niinomi, Toshiyasu Matsushima, Shigeichi Hirasawa

      vol.J87-A ( no.2 ) 224 - 233  2004  [Refereed]

  • A source model with probability distribution over word set and recurrence time theorem

    M Goto, T Matsushima, S Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E86A ( 10 ) 2517 - 2525  2003.10  [Refereed]

  • 直交計画を用いたブール関数の学習に関する一考察

    浮田善文, 松嶋敏泰, 平澤茂一

    電子情報通信学会論文誌   J86-A ( 4 ) 482 - 490  2003.04

    CiNii

  • 情報理論からの学習,帰納推論,予測 (特集 情報論的学習理論--機械学習のさまざまな形)

    松嶋敏泰

    Computer today   20 ( 2 ) 5 - 10  2003.03

    CiNii J-GLOBAL

  • A parallel iterative decoding algorithm for zero-tail and tail-biting convolutional codes

    T Matsushima, TK Matsushima, S Hirasawa

    2003 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY - PROCEEDINGS     175 - 175  2003

  • メモリ量を低減した近似ベイズ符号化アルゴリズム

    野村亮, 松嶋敏泰, 平澤茂一

    電子情報通信学会論文誌   J86-A ( 1 ) 46 - 59  2003.01

    CiNii

  • ウェーブレットパケット基底を用いた信号推定におけるベイズ決定理論の適用に関する一考察

    北原正樹, 野村亮, 松嶋敏泰

    電子情報通信学会論文誌(A) Vol.J85   J85-A ( 5 ) 584 - 596  2002.05

    CiNii

  • An alternate algorithm for calculating generalized posterior probability and decoding

    T Matsushima, TK Matsushima, S Hirasawa

    ISIT: 2002 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, PROCEEDINGS     338 - 338  2002

  • On the generalized viterbi algorithm using likelihood ratio testing

    T Niinomi, T Matsushima, S Hirasawa

    ISIT: 2002 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, PROCEEDINGS     366 - 366  2002

  • An analysis of the difference of code lengths between two-step codes based on MDL principle and Bayes codes.

    Masayuki Goto, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE Transactions on Information Theory   47 ( 3 ) 927 - 944  2001.03  [Refereed]

    DOI

    Scopus

    7
    Citation
    (Scopus)

  • 情報論的学習理論における数理モデル

    松嶋敏泰

    人工知能学会誌   16   252 - 255  2001.03

  • A study of the decision of control parameters for adaptive automatic-repeat request strategy

    K Tsukamoto, T Matsushima, S Hirasawa

    ELECTRONICS AND COMMUNICATIONS IN JAPAN PART I-COMMUNICATIONS   84 ( 11 ) 61 - 70  2001  [Refereed]

    　View Summary

    Ill many practical transmission systems, transmission error rate of the channel is time-varying. In previous works for controlling the rime-varying channel, the state of the channel is estimated and is uniquely determined. Then, the optimum value is chosen as a control parameter for the determined state. However, there is a discrepancy between the actual channel state and estimated state. The optimum control parameter determined for the estimated state does not necessarily provide the best performance presented by some object function in error control such as throughput efficiency. In th is study, the expected value of throughput is calculated by using the posterior probability for each state and an algorithm in which the control parameter is selected to maximize the expected performance is proposed. From the viewpoint of the statistical decision theory, it is shown that this selection is the optimum in maximizing the throughput under the Bayes criterion. Using simulation, the proposed method is evaluated and its effectiveness is shown. (C) 2001 Scripta Technica

  • An Iterative Algorithm for Calculating Posterior Probability and Model Representation

    MATSUSHIMA T.

    Proceedings of IEEE Int. Symp. on Information Theory, 2001    2001

    CiNii

  • Mathematical Models in Information-Based Induction Science

    Toshiyasu Matsushima

    Journal of the Japanese Society for Artificial Intelligence   vol.16 ( no.2 ) 252 - 255  2001  [Refereed]

  • 損失関数を考慮した拡張事後密度の漸近正規性

    後藤正幸, 松嶋敏泰, 平澤茂一

    電子情報通信学会論文誌   J83-A ( 6 ) 639 - 650  2000.06

    CiNii

  • ベイズ決定理論に基づく統計的モデル選択の選択誤り確率に関する解析

    GOTOH Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    日本経営工学会   50 ( No.6 ) 475 - 485  2000.02

    CiNii

  • On Analysis of noiseless decision feedback scheme using fixed size list decoder for tree codes

    T Niinomi, T Matsushima, S Hirasawa

    2000 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, PROCEEDINGS     231 - 231  2000

    　View Summary

    In this paper, the generalized proof are shown for the coding theorem of [1]. Consequently, the further discussion is obtained.

  • Achievable rates of random number generators for an arbitrary prescribed distribution from an arbitrary given distribution

    T Yoshida, T Matsushima, S Hirasawa

    2000 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, PROCEEDINGS     155 - 155  2000

    　View Summary

    In this paper, we show maximal rates in the case that random number generators generate a random sequence with an arbitrary prescribed distribution from a random sequence with an arbitrary given distribution.

  • On the variance and the probability of length overflow of lossless codes

    R Nomura, T Matsushima, S Hirasawa

    2000 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, PROCEEDINGS     44 - 44  2000

    　View Summary

    In this paper, we show the probability of length overflow of several codes by using the variance and the asymptotic normality of the codelength.

  • 木符号におけるリスト復号法を用いた判定帰還方式について

    電子情報通信学会論文誌/電子情報通信学会   J83-A ( No.1 ) 67 - 82  2000.01

  • 不確実な知識を用いた推論のモデル化と推論法について

    情報処理学会論文誌/情報処理学会   41 ( No.1 ) 1 - 11  2000.01

  • Almost sure and mean convergence of extended stochastic complexity

    M Gotoh, T Matsushima, S Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E82A ( 10 ) 2129 - 2137  1999.10  [Refereed]

    　View Summary

    We analyse the extended stochastic complexity (ESC) which has been proposed by K. Yamanishi. The ESC can be applied to learning algorithms for on-line prediction and batch-learning settings. Yamanishi derived the upper bound of ESC satisfying uniformly for all data sequences and that of the asymptotic expectation of ESC. However, Yamanishi concentrates mainly on the worst case performance and the lower bound has not been derived. In this paper, we show some interesting properties of ESC which are similar to Bayesian statistics: the Bayes rule and the asymptotic normality. We then derive the asymptotic formula of ESC in the meaning of almost sure and mean convergence within an error of o(1) using these properties.

  • On decoding methods beyond the BCH bound and their applications to soft-decision decoding

    Manabu Kobayashi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Electronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi)   82 ( 9 ) 39 - 51  1999.09  [Refereed]

    　View Summary

    For the two-dimensional BCH code, several decoding methods exceeding the BCH bound and correcting the errors that cannot be corrected by the conventional limited distance decoding method have been proposed. This article proposes an algorithm that allows reduction of the computational volume in a decoding method exceeding the BCH bound by solving the equation for unknown variables beforehand and limiting the range of the error location. Further, this decoding method exceeding the BCH bound is applied to soft-decision decoding methods that use limited-distance decoding multiple times, and especially to Chase decoding, the decoding of Tanaka et al., and that of Kaneko et al. It is shown that the amount of computation and the decoding error rate are improved.

    DOI

    Scopus

  • 電子情報通信用語辞典

    コロナ社    1999.07

  • The Generalization of Bayesian Network's Deductive Method

    Daiki Koizumi, Yoshifumi Ukita, Toshiyasu Matsushima

    The 1999 Sigma Xi, The Scientific Research Society, Florida Tech Chapter    1999.04

  • On a Deductive Reasoning Model and Method for Uncertainty.

    Makoto Suzuki, Toshiyasu Matsushima, Shigeichi Hirasawa

    11th IEEE International Conference on Tools with Artificial Intelligence(ICTAI)     161  1999

    DOI

  • 事前分布が異なる場合のMDL原理に基づく符号とベイズ符号の符号長に関する解析

    GOTOH Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会論文誌   J82-A ( 5 ) 698 - 708  1999

    CiNii

  • マルコフ情報源に対し誤り伝播を抑えるVF符号に関する一考察

    KIMURA Masaru, GOTOH Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会論文誌   J82-A ( 5 ) 736 - 741  1999

    CiNii

  • BCH限界を超える復号アルゴリズムを用いた2元BCH符号の軟判定復号法

    KOBAYASHI Manabu, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会論文誌   J82-A ( 4 ) 539 - 549  1999

    CiNii

  • A generalization of B.S. Clarke and A.R. Barron's asymptotics of Bayes codes for FSMX sources

    M Gotoh, T Matsushima, S Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E81A ( 10 ) 2123 - 2132  1998.10  [Refereed]

    　View Summary

    We shall generalize B.S. Clarke and A.R. Barron's analysis of the Bayes method for the FSMX sources. The FSMX source considered here is specified by the set of all states and its parameter value. At first, we show the asymptotic codelengths of individual sequences of the Bayes codes for the FSMX sources. Secondly, we show the asymptotic expected codelengths. The Bayesian posterior density and the maximum likelihood estimator satisfy asymptotic normality for the finite ergodic Markov source, and this is the key of our analysis.

  • Parallel architecture for generalized LFSR in LSI built-in self testing

    TK Matsushima, T Matsushima, S Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E81A ( 6 ) 1252 - 1261  1998.06  [Refereed]

    　View Summary

    This paper presents a new architecture for multiple-input signature analyzers. The proposed signature analyzer with H delta inputs is designed by parallelizing a GLFSR(delta, m), where delta is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for representing LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e.g., SISRs, MISRs, multiple MISRs and MLFSRs. It is shown that a proposed signature analyzer with H delta inputs requires less complex hardware than either single GLFSR(H delta, m)s or a parallel construction of the H original GLFSR(delta, m)s. It is also shown that the proposed signature analyzer, while requiring simpler hardware, has comparable aliasing probability with analyzers using conventional GLFSRs for some CUT error models of the same test response length and test lime. The proposed technique would be practical for testing CUTs with a large number of output sequences, since the test circuit occupies a smaller area on the LSI chip than the conventional multiple-input signature analyzers of comparable aliasing probability.

  • Parallel architecture for generalized LFSR in LSI built-in self testing

    TK Matsushima, T Matsushima, S Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E81A ( 6 ) 1252 - 1261  1998.06  [Refereed]

    　View Summary

    This paper presents a new architecture for multiple-input signature analyzers. The proposed signature analyzer with H delta inputs is designed by parallelizing a GLFSR(delta, m), where delta is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for representing LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e.g., SISRs, MISRs, multiple MISRs and MLFSRs. It is shown that a proposed signature analyzer with H delta inputs requires less complex hardware than either single GLFSR(H delta, m)s or a parallel construction of the H original GLFSR(delta, m)s. It is also shown that the proposed signature analyzer, while requiring simpler hardware, has comparable aliasing probability with analyzers using conventional GLFSRs for some CUT error models of the same test response length and test lime. The proposed technique would be practical for testing CUTs with a large number of output sequences, since the test circuit occupies a smaller area on the LSI chip than the conventional multiple-input signature analyzers of comparable aliasing probability.

  • 矛盾を含む知識の取り扱いについての一考察

    SAITO Mikiya, UKITA Yoshifumi, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi, Mikiya Saito, Yoshifumi Ukita, Toshiyasu Matsushima, Shigeichi Hirasawa, Department of Industrial and Management Systems Engineering School of Science and Engineering Waseda University, Department of Industrial and Management Systems Engineering School of Science and Engineering Waseda University, Department of Industrial and Management Systems Engineering School of Science and Engineering Waseda University, Department of Industrial and Management Systems Engineering School of Science and Engineering Waseda University

    人工知能学会誌   13 ( 2 ) 252 - 262  1998.03

    CiNii

  • Non-Hierarchical Clustering using Genetic Algorithm(GA) and K-means Method

    李相協, 松嶋敏泰, 平沢茂一

    日本経営工学会春季大会予稿集   1998  1998

    J-GLOBAL

  • A Universal Code Considering the Codeword Cost

    YOSHIDA T.

    Proc.of Int.Symp.on Inf.Theory and its Applications     165 - 168  1998

    CiNii

  • Type for hierarchical probability model class and universal coding

    T Matsushima, S Hirasawa

    1998 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY - PROCEEDINGS     319 - 319  1998

  • On error rates of statistical model selection based on information criteria

    H Gotoh, T Matsushima, S Hirasawa

    1998 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY - PROCEEDINGS     417 - 417  1998

    　View Summary

    In this paper, we shall derive the upper bounds on error rates of the statistical model selection using the information criteria, P(e)*. The similar bounds were derived by J.Suzuki [2]. We shall generalize the results for the general model class.

  • The Optimal Algorithms for the Reinforcement Learning Problem Separated into a Learning Period and a Contorol Period

    MAEDA Yasunari, UKITA Yoshihumi, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    Transactions of Information Processing Society of Japan   39 ( 4 ) 1116 - 1126  1998

    　View Summary

    In this paper, new algorithms are proposed based on statistical decision theory in the field of Markov decision processes under the condition that a tradition probability matrix is unknown. In previous researches on RL(reinforcement learning), learning is based on only the estimation of an unknown transition probability matrix and the maximum reward is not received in a finite period, though their purpose is to maximize a reward. In our algorithms it is possible to maximize the reward within a finite period with respect to Bayes criterion. Moreover, we propose some techniques to reduce the computational complexity of our algorithm from exponential order to polynomial order.

    CiNii

  • A Note on Decision Theoretic Formulation for Learning from Queries

      39 ( 11 ) 2937 - 2948  1998

  • 適応型ARQにおける制御パラメータ決定方式について

    TSUKAMOTO Ken-ichiro, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会論文誌   J81-B-1 ( 6 ) 391 - 400  1998

    CiNii

  • 質問からの学習問題の決定理論による定式化に関する一考察

    情報処理学会論文誌   39 ( 11 ) 2937 - 2948  1998

    CiNii

  • 学習期間と制御期間に分割された強化学習問題における最適アルゴリズムの提案(共著)

    MAEDA Yasunari, UKITA Yoshihumi, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    情報処理学会論文誌   39 ( 4 ) 1116 - 1126  1998

    　View Summary

    In this paper, new algorithms are proposed based on statistical decision theory in the field of Markov decision processes under the condition that a tradition probability matrix is unknown. In previous researches on RL(reinforcement learning), learning is based on only the estimation of an unknown transition probability matrix and the maximum reward is not received in a finite period, though their purpose is to maximize a reward. In our algorithms it is possible to maximize the reward within a finite period with respect to Bayes criterion. Moreover, we propose some techniques to reduce the computational complexity of our algorithm from exponential order to polynomial order.

    CiNii

  • BCH限界を超える復号法とその軟判定復号法への応用(共著)

    KOBAYASHI Manabu, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会論文誌   J81-A ( 4 ) 751 - 762  1998

    CiNii

  • Berlekamp-Masseyアルゴリズムを用いたBCH限界を超える復号法の計算量について

    KOBAYASHI Manabu, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会論文誌A   vol.J80 ( 9 ) 1554 - 1558  1997.09

    CiNii

  • New architecture of signature analyzers for multiple-output circuits

    Tomoko K. Matsushima, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics   4   3900 - 3905  1997

    　View Summary

    This paper presents a new architecture for multiple-input signature analyzers. The proposed signature analyzer with Hδ inputs is designed by parallelizing a GLFSR(δ, m), where δ is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for representing LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e.g., SISRs, MISRs, multiple MISRs and MLFSRs. It is shown that a proposed signature analyzer with Hδ inputs requires less complex hardware than either single GLFSR(Hδ, m)s or parallel construction H original GLFSR(δ, m)s. It is also shown that the proposed parallelization technique can be applied to a test pattern generator in BIST, since the GLFSR is also used to generate patterns for a CUT. The proposed technique would be practical for testing CUTs with a large number of input and output sequences, since the test circuit occupies a smaller area on the LSI chip than conventional test circuits.

  • Machine learning by a subset of hypotheses

    Takafumi Mukouchi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics   3   2533 - 2538  1997

    　View Summary

    Bayesian theory is effective in statistics, lossless, source coding, machine learning, etc. It is often, however, computationally expensive since the calculation of posterior probabilities and of mixture distributions is not tractable. In this paper, we propose a new method for approximately calculating mixture distributions in a discrete hypothesis class.

  • Machine learning by a subset of hypotheses

    T Mukouchi, T Matsushima, S Hirasawa

    SMC '97 CONFERENCE PROCEEDINGS - 1997 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5     2533 - 2538  1997

    　View Summary

    Bayesian theory is effective in statistics, lossless source coding, machine learning, etc. It is often, however, computationally expensive since the calculation of posterior probabilities and of mixture distributions is not tractable. In this paper, we propose a new method for approximately calculating mixture distributions in a discrete hypothesis class.

  • A new architecture of signature analyzers for multiple-output circuits

    TK Matsushima, T Matsushima, S Hirasawa

    SMC '97 CONFERENCE PROCEEDINGS - 1997 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5     3900 - 3905  1997

    　View Summary

    This paper presents a near architecture for multiple-input signature analyzers. The proposed signature analyzer with H delta inputs is designed by parallelizing a GLFSR(delta,m), where delta is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for rep resenting LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e.g., SISRs: MISRs, multiple MISRs and MLFSRs. It is show that a proposed signature analyzer with HS inputs requires less complex hardware than either single GLFSR(H delta,m)s or parallel construction H original GLFSR(delta,m)s. It is also shown that the proposed parallelization technique can be applied to a test pattern generator in BIST, since the GLFSR is also used to generate patterns for a CUT. The proposed technique would be practical for testing CUTs with a large number of input and output sequences, since the test circuit occupies a smaller area on the LSI chip than conventional test circuits.

  • Machine learning by a subset of hypotheses

    T Mukouchi, T Matsushima, S Hirasawa

    SMC '97 CONFERENCE PROCEEDINGS - 1997 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5     2533 - 2538  1997

    　View Summary

    Bayesian theory is effective in statistics, lossless source coding, machine learning, etc. It is often, however, computationally expensive since the calculation of posterior probabilities and of mixture distributions is not tractable. In this paper, we propose a new method for approximately calculating mixture distributions in a discrete hypothesis class.

  • A learning with membership queries to minimize prediction error

    Y Ukita, T Matsushima, S Hirasawa

    SMC '97 CONFERENCE PROCEEDINGS - 1997 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5     4412 - 4417  1997

    　View Summary

    In this paper, we consider the problem to predict the class of an unknown sample after learning from queries, We propose to evaluate a learning algorithm by a loss function for the prediction under a constraint, In this paper, the error probability for the prediction and the number of queries is defined as the loss function and the constraint, respectively, Then our objective is to minimize the error probability, the error probability is determined by what presentation order for instances to query and how to predict, Since the optimal prediction has been shown in previous researches, we only have to select the optimal presentation order for instances to query, We propose a lower bound used in the branch-and-bound algorithm to select the optimal presentation order for instances, Lastly, we show the efficiency of the algorithm using the derived lower bound by numerical computation.

  • Asymptotic property of sufficient statistic codes

    Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE International Symposium on Information Theory - Proceedings     421  1997

    　View Summary

    In this paper, we obtain an accurate asymptotic formula of the Bayes optimal codelength in the case that the sources are not always i.i.d. sources by deriving the asymptotic codelength of sufficient statistic codes. © 1997 IEEE.

    DOI

    Scopus

  • The 55th Technical Comference(<Features>Frontiers of QC Activities in Production Fields)

    Toshiyasu Matsushima

      vol.27 ( no.4 ) 65 - 78  1997

  • Based on Bayes Statistics the On-line Learning Model and its Learnability

    Makoto Nakazawa, Toshiyasu Matsushima, Shigeichi Hirasawa

    情報処理学会全国大会講演論文集   55th ( 2 ) 519 - 520  1997

    J-GLOBAL

  • Document retrieval models using keywords

    Tsuneji Futagami, Toshiyasu Matsushima, Shigeichi Hirasawa

    情報処理学会全国大会講演論文集   55th ( 1 ) 257 - 258  1997

    J-GLOBAL

  • Parallel encoder and decoder architecture for cyclic codes

    TK Matsushima, T Matsushima, S Hirasawa

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E79A ( 9 ) 1313 - 1323  1996.09  [Refereed]

    　View Summary

    Recently, the high-speed data transmission techniques that have been developed for communication systems have in turn necessitated the implementation of high-speed error correction circuits. Parallel processing has been found to be an effective method of speeding up operations, since the maximum achievable clock frequency is generally bounded by the physical constraints of the circuit. This paper presents a parallel encoder and decoder architecture which can be applied to both binary and nonbinary cyclic codes. The architecture allows H symbols to be processed in parallel, where H is an arbitrary integer, although its hardware complexity is not proportional to the number of parallel symbols H. As an example, we investigate hardware complexity for a Reed-Solomon code and a binary BCH code. It is shown that both the hardware complexity and the delay for a parallel circuit is much less than that with the parallel operation of H conventional circuits. Although the only problem with this parallel architecture is that the encoder's critical path length increases with H, the proposed architecture is more efficient than a setup using H conventional circuits for high data rate applications. It is also suggested that a parallel Reed-Solomon encoder and decoder, which can keep up with optical transmission rates, i.e., several giga bits/sec, could be implemented on one LSI chip using current CMOS technology.

  • 統計モデル選択の概要

    松嶋敏泰

    オペレーションズ・リサーチ   41 ( 7 ) 369 - 374  1996

    CiNii J-GLOBAL

  • A Bayes coding algorithm for FSMX soureces

    MATSUSHIMA T.

    Proc. Int. Symp. of Information Theory, 1995    1995

    CiNii

  • A two-stage universal coding procedure using sufficient statistics

    T Matsushima, S Hirasawa

    PROCEEDINGS 1995 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY     17 - 17  1995

  • A Bayes coding algorithm for FSM sources

    T Matsushima, S Hirasawa

    PROCEEDINGS 1995 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY     388 - 388  1995

  • 知識情報処理の基礎とその応用研究部会

    Shigeichi Hirasawa, Toshiyasu Matsushima

      vol.5 ( no.2 ) 140 - 142  1995

    J-GLOBAL

  • On Knowledge Representation and Reasoning System with a Range of Certainty Factors

    SUZUKI Makoto, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IPSJ Journal   35 ( 5 ) 691 - 705  1994.05

    　View Summary

    We discuss the method for representing uncertain knowledge information and also on a reasoning system that guarantees a given reliability based on information theory and probability theory. In this paper, we propose a new reasoning system which consists of inductive and deductive inferences, by using a knowledge representation method with a range of certainty factors. In inductive inference, a new atom is computed from the observed data or facts, together with the upperbound and lowerbound between which its probability must fall. Also in deductive inference, which includes negation, conjunction, disjunction, chain and modus ponens, a new atom is deduced with a range of certainty factors computed from the results of inductive inference. Properties and behaviors of the system are clarified. It can be concluded that the new reasoning system is effective of conventional expert systems.

    CiNii

  • On block coded ARQ schemes cumulating the rejected sequences

    Toshihiro Niinomi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE International Symposium on Information Theory - Proceedings     376  1994  [Refereed]

    　View Summary

    We show that the received sequences, which are rejected and not discarded on ARQ schemes, make the next decision with repeat request powerful by a random coding arguments. We first give the ordinary ARQ of the basic algorithm with some criterion, and define the ARQ with cumulating the rejected sequences, which naturally extended from the ordinary one. Then we study the error exponent of decoding the second received sequences under the condition that the first is rejected. We assume the block coded ARQ with noiseless feedback. © 1994 IEEE.

    DOI

    Scopus

  • A Bayes coding algorithm using context tree

    Toshiyasu Matsushima, Shigeichi Hirasawa

    IEEE International Symposium on Information Theory - Proceedings     386  1994  [Refereed]

    　View Summary

    The context tree weighting (CTW) algorithm [Willems et al., 1993] has high compressibility for universal coding with respect to FSMX sources. The present authors propose an algorithm by reinterpreting the CTW algorithm from the viewpoint of Bayes coding. This algorithm can be applied to a wide class of prior distribution for finite alphabet FSMX sources. The algorithm is regarded as both a generalized version of the CTW procedure and a practical algorithm using a context tree of the adaptive Bayes coding which has been studied in Mataushima et al. (1991). Moreover, the proposed algorithm is free from underflow which frequently occurs in the CTW procedure. © 1994 IEEE.

    DOI

    Scopus

  • An inductive inference procedure to minimize prediction error.

    Toshiyasu Matsushima, Hiroshige Inazumi, Shigeichi Hirasawa

    IEEE Transactions on Systems, Man, and Cybernetics   23 ( 2 ) 547 - 554  1993.03  [Refereed]

    DOI

    Scopus

  • Learning formal languages from Feasible Teachers

    Tetsuya Sakai, Shigeichi Hirasawa, Toshiyasu Matsushima

    Journal of Japan Industrial Management Association   vol.4 ( no.3 ) 245 - 245  1993

    CiNii

  • 信頼性を考慮した推論について

    Makoto Suzuki, Toshihiro Niinomi, Shigeichi Hirasawa, Toshiyasu Matsushima

    日本経営工学会春季大会予稿集   vol.44 ( no.3 ) 245 - 245  1993

    CiNii J-GLOBAL

  • Inductive and Deductive Inference from the View Point of Information

    Toshiyasu Matsushima

    Memoirs of the school of Sci.& Eng. Waseda Univ.   vo.57   237 - 254  1993

  • A Model for Learning from a View Point of Information Theory

    Production Research 1993   17,385  1993

  • 不確実性をもつ論理式の帰納推論に関する一考察

    情報処理学会論文誌   33 ( 12 ) 1461 - 1475  1992.12

  • 帰納推論の情報理論による定式化と最適化

    Toshiyasu Matsushima

    横浜商大論集   25 ( 1-2 ) 120 - 188  1992

    CiNii

  • MDLの帰納推論への応用

    人工知能学会誌   7 ( 4 ) 615 - 621  1992

  • A class of distortionless codes designed by Bayes decision theory.

    Toshiyasu Matsushima, Hiroshige Inazumi, Shigeichi Hirasawa

    IEEE Transactions on Information Theory   37 ( 5 ) 1288 - 1293  1991.09  [Refereed]

    DOI

    Scopus

    52
    Citation
    (Scopus)

  • 不確実性をもつ仮説に関する帰納推論

    Toshiyasu Matsushima, Hiroshige Inazumi, Shigeichi Hirasawa

      vol.42 ( no.3 ) 212 - 212  1991

    CiNii J-GLOBAL

  • A CLASS OF NOISELESS CODES DESIGNED BY DECISION THEORY

    Toshiyasu Matsushima

      vol.7   381 - 405  1991

  • 情報理論による不確実な知識の表現法と推論に関する一考察

    松嶋敏泰, 鈴木譲, 稲積宏誠, 平沢茂一, 石渡徳弥

    早稲田大学理工学研究所報告   131 ( 131 ) p38 - 51  1991

    CiNii J-GLOBAL

  • An efficient user interface based on maximizing shared information

    Joe Suzuki, Toshiyasu Matsushima, Shigeichi Hirsawa, Hiroshige Inazumi

    Electronics and Communications in Japan (Part III: Fundamental Electronic Science)   73 ( 5 ) 40 - 49  1990  [Refereed]

    　View Summary

    In designing systems with a human‐computer interface with a minimum number of interactions, there are two issues to consider: the determination of a proper sequence of questions by the user, and proper termination by the computer system, based on previous instructions. In short, these issues are those of feature selection ordering and a stopping rule for pattern recognition processes. Conventional treatments of these problems have been investigated from the viewpoint of an average error rate. When the number of patterns is large, however, and the number of instructions to be terminated is large, from the point of view of user interface efficiency, and the average error rate is not an effective indicator at the intermediate stage. In this paper, a new method is proposed for determining feature selection ordering and a stopping rule which focuses on the remaining patterns at each stage, and which maximizes the value of mutual information between the user's responses and the required pattern. Important properties associated with this scheme have been demonstrated while evaluating its performance via computer simulation. One is that the average information gain at each stage decreases monotonically, and another is that this scheme produces the minimum error rate. Copyright © 1990 Wiley Periodicals, Inc., A Wiley Company

    DOI

    Scopus

  • Inductive Inference scheme at a Finite Stage of Process from View Point of Source Coding

    MATSUSHIMA T.

    信学論(E)   73E ( 5 ) 644 - 652  1990

    CiNii

  • Stopping rules based on a posteriori probability for every pattern and every stage

    Joe Suzuki, Toshiyasu Matsushima, Shigeichi Hirasawa, Hiroshige Inazumi

    Electronics and Communications in Japan (Part III: Fundamental Electronic Science)   72 ( 8 ) 71 - 82  1989  [Refereed]

    DOI

    Scopus

  • 相互情報量最大に基準を置くユーザインタフェースの効率化

    Joe Suzuki, Toshiyasu Matsushima, Hiroshige Inazumi, Shigeichi Hirasawa

      vol.J72-A ( no.3 ) 517 - 524  1989  [Refereed]

    CiNii

  • 情報理論に基づく推論の体系化と不確実な知識表現への応用

    Toshiyasu Matsushima, Joe Suzuki, Hiroshige Inazumi, Shigeichi Hirasawa

    日本経営工学会春季大会予稿集   vol.40 ( no.3 ) 196 - 196  1989

    J-GLOBAL

  • Applications of Information Theory into Predicate Logic for AI Systems

    IEICE TRANSACTIONS   Vol.E72-E ( No.5 ) 443 - 451  1989

  • Design method of intelligent interface for minimizing the number of questions and answers

    Joe Suzuki, Toshiyasu Matsushima, Shigeichi Hirasawa, Hiroshige Inazumi

    Bulletin of Centre for Informatics (Waseda University)   8   41 - 48  1988.09

    J-GLOBAL

  • パターンごと・ステージごとに事後確率のしきい値をおくストッピングルール

    Joe Suzuki, Toshiyasu Matsushima, Hiroshige Inazumi, Shigeichi Hirasawa

      vol.J71-A ( no.6 ) 1299 - 1308  1988  [Refereed]

    CiNii

  • 質問応答回数最小をねらいとした効率的な知的インタフェイスの設計

    Joe Suzuki, Toshiyasu Matsushima, Hiroshige Inazumi, Shigeichi Hirasawa

      vol.39 ( no.3 ) 191 - 191  1988

    CiNii

  • あいまいな命題を含む推論モデルに関する一考察

    Toshiyasu Matsushima

    日本経営工学会秋季研究大会予稿集   vol.37 ( no.5 ) 326 - 326  1986

    DOI CiNii J-GLOBAL

  • Asymptotic Property of Universal Lossless Coding for Independent Piecewise Identically Distributed Sources

      - 1

  • Variable-Length Lossy Compression Allowing Positive Overflow and Excess Distortion Probabilities

    ISIT2017  

  • Parallel Concatenation of Polar Codes and Iterative Decoding

     

  • Asymptotics of MLE - based Prediction for Semi - supervised learning

     

  • On the Bayesian Forecasting Algorithm under the Non-Stationary Binomial Distribution with the Hyper Parameter Estimation

     

  • A Formalization of Generalized Probabilistic Reasoning and Its Procedure on Junction Trees

     

  • On the Hyperparameter Estimation of Time Varying Poisson Model for Bayesian WWW Traffic Forecasting

     

  • Multiuser Detection Algorithm for CDMA based on the Belief Propagation Algorithm

     

  • On the evaluation of the achievable codelength of Fixed-length codes

     

  • A Note on Relation Between the Fourier Coefficients and the Interaction Effects in the Experimental Design

     

  • A Note on Linear Programming Based Communication Receivers

     

  • On Uncertain Logic Based upon Information Theory

     

  • On the Optimal Inductive Inference Scheme from the View Point of Source Coding

     

  • An analysis on Difference between the Code based on MDL Principle and the Bayes Code(共著)

     

  • A Note on Concept Learning with Membership Queries(共著)

     

  • Asymptotic Property of Sufficient Statistic Codes

     

  • A Study on Difference of Codelength between MDL Codes and Bayes Codes in Case Different Prior are Assumed(共著)

     

  • A Learning with Membership Queries to Minimize Prediction Error(共著)

     

  • A study on difference of codelenghs between MDL codes and Bayes codes on case different priors are assumed

     

  • On a Reasoning Model with a Knowledge Representation Matrix for Uncertainty

     

  • Non-Hierarchical Clustering using Genetic Algorithm (GA) and K-means Method

     

  • Iterative Soft-Decision Decoding Using an Update Algorithm of Error-Locator Polynomial for Binary BCH Codes

     

  • Consistency of Bayesian Model Selection

     

  • Compression of File for Document Retrieval System

     

  • An Approximation Algorithm of Bayes Coding for FSMX sources

     

  • A Note on Learning of Probabilistic Hypotheses from Membership Queries

     

  • An interpretation of Turbo decoding from the viewpoint of differential geometry

     

  • On the evaluation of the achievable codelength of Fixed-length codes

     

  • A Note on Spelling Correction Methods based upon Statistical Decision Theory

     

  • An Information Spectrum Consideration on the Universal Joint Source-Channel Coding

     

  • A Note on the Branch-and-Cut Approach to Decoding Linear Block Codes

     

  • A Description of Experimental Design using an Orthonormal System

     

  • Linear Programming Bounds of Orthogonal Arrays for Experimental Designs

     

  • Bayes universal source coding scheme for correlated sources

     

▼display all

Books and Other Publications

  • 写像とグラフによる統一的体系化 : 変数/定数の観測可能性の視点から

    早稲田大学データ科学教育チーム, 松嶋, 敏泰

    サイエンス社  2025.04 ISBN: 9784781916293

  • モデルの候補が複数あるときの意思決定

    早稲田大学データ科学教育チーム, 松嶋, 敏泰

    サイエンス社  2024.04 ISBN: 9784781915982

  • 特徴記述・構造推定・予測 : 回帰と分類を例に

    早稲田大学データ科学教育チーム, 松嶋, 敏泰

    サイエンス社  2023.03 ISBN: 9784781915678

  • データに基づく意思決定の基礎

    早稲田大学データ科学教育チーム, 松嶋, 敏泰

    サイエンス社  2022.04 ISBN: 9784781915401

  • データ科学入門 : データに基づく意思決定の基礎

    松嶋, 敏泰, 早稲田大学データ科学教育チーム

    サイエンス社  2022.04 ISBN: 9784781915401

Presentations

  • Optimal Estimating of the Magnitude of the change for Sources with Piecewise Constant Parameters under Bayesian Criterion

    Kairi Suzuki, Akira Kamatsuka, Toshiyasu Matsushima

    Bayes on the Beach 

    Presentation date： 2019.11

  • Bayes Optimal Prediction and Its Approximative Algorithm on Model Including Cluster Explanatory Variables and Regression Explanatory Variables

    Haruka Murayama, Shota Saito, Yuta Nakahara, Toshiyasu Matsushima

    Presentation date： 2019.07

  • Bayes Optimal Classification on Decision Tree Model and Its Approximative Algorithm Using Ensemble Learning

    Nao Dobashi, Shota Saito, Toshiyasu Matsushima

    Presentation date： 2019.07

  • A Note on Mixed Level Experimental Designs Using Augmented Orthogonal Arrays

    Junki Yamaguchi, Koki Kazama, Akira Kamatsuka, Shota Saito, Toshiyasu Matsushima

    Presentation date： 2019.07

  • 攻撃者の目的と背景知識を明確にしたプライバシ保護を考慮した情報公開

    鎌塚明, 宮下有咲, 吉田隆弘, 松嶋敏泰

    みずほ銀行・早稲田大学 学術交流協定締結1周年記念シンポジウム ポスターセッション 

    Presentation date： 2019.07

  • i.p.i.d.情報源におけるベイズ規準の下で最適な変化回数の推定

    鈴木海理, 鎌塚明, 松嶋敏泰

    電子情報通信学会 技術研究報告 IBISML 

    Presentation date： 2019.06

  • Gradient Coding based on LDGM Codes and Stochastic Gradient Descent

    Presentation date： 2019.03

  • 相異なる3元ハフマン符号が構成される2値無記憶拡大情報源の条件に関する一検討

    宮希望, 吉田隆弘, 地主創

    第41回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2018.12

  • Non-Asymptotic and Asymptotic Fundamental Limits of Guessing Subject to Distortion

    Presentation date： 2018.12

  • $(n,k,d,r,t,x,y)_{q}$ LRC符号の最小距離および次元の限界式に関する一考察

    風間皐希, 鎌塚明, 松嶋敏泰

    第41回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2018.12

  • 拡張直交配列を利用した多水準の実験計画法に関する一考察

    山口純輝, 風間皐希, 鎌塚明, 齋藤翔太, 松嶋敏泰

    第41回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2018.12

  • メロディの生成数理モデルを仮定した自動作曲

    西川史織, 中原悠太, 松嶋敏泰

    第41回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2018.12

  • 富士山型空間結合符号に対するCovariance Evolution

    中原悠太, 松嶋敏泰

    第41回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2018.12

  • 攻撃者の目的と背景知識を明確にしたプライバシ保護を考慮した情報公開

    宮下有咲, 鎌塚 明, 吉田隆弘, 松嶋敏泰

    第41回情報理論とその応用シンポジウム予稿集（SITA2018） 

    Presentation date： 2018.12

  • 一般化ラベルノイズの下での分類に関する漸近評価

    安田豪毅, 須子統太, 小林学, 松嶋敏泰

    電子情報通信学会技術研究報告. IBISML，情報論的学習理論と機械学習 

    Presentation date： 2018.11

  • パラメータ未知の一般化ラベルノイズモデルにおける分類法について

    須子統太, 安田豪毅, 堀井俊佑, 小林学

    電子情報通信学会技術研究報告. IBISML，情報論的学習理論と機械学習 

    Presentation date： 2018.11

  • 統計的決定理論に基づいた因果効果の推定法に関する一考察

    堀井俊佑, 須子統太

    電子情報通信学会研究技術報告 

    Presentation date： 2018.11

  • A Note on a Bound on the Rate of a Locally Recoverable Code with Multiple Recovering Sets

    Kazama, Koki, Kamatsuka, Akira, Yoshida, Takahiro, Matsushima, Toshiyasu

    Proceedings of 2018 International Symposium on Information Theory and Its Applications 

    Presentation date： 2018.10

  • Expected Graph Evolution for Spatially “Mt. Fuji” Coupled LDPC Codes

    Nakahara, Yuta, Matsushima, Toshiyasu

    Proceedings of 2018 International Symposium on Information Theory and Its Applications 

    Presentation date： 2018.10

  • On Distance Properties of (r, t, x)-LRC Codes（最新論文紹介セッション）

    風間皐希, 松嶋敏泰

    第7回誤り訂正符号のワークショップ 

    Presentation date： 2018.09

  • Concatenated Spatially Coupled LDPC Codes for Joint Source-Channel Coding（最新論文紹介セッション）

    中原悠太, 松嶋敏泰

    第7回誤り訂正符号のワークショップ 

    Presentation date： 2018.09

  • ランク誤りを考慮した Coded Computation に関する一考察

    風間皐希, 鎌塚明, 松嶋敏泰

    データ科学総合研究教育センター第3回シンポジウム（ポスター発表） 

    Presentation date： 2018.07

  • 潜在変数に階層モデルを仮定したベイズ独立成分分析

    浅葉海, 齋藤翔太, 堀井俊佑, 松嶋敏泰

    電子情報通信学会技術研究報告  電子情報通信学会情報論的学習理論と機械学習研究会（IBISML）

    Presentation date： 2018.03

  • 陽に記述された画像生成モデルに対するベイズ基準のもと最適な可逆符号化

    中原悠太, 松嶋敏泰

    映像情報メディア学会2017年冬季大会講演予稿集  映像情報メディア学会

    Presentation date： 2017.12

  • 微少なアンダーフロー確率を許した可変長intrinsic randomness問題

    吉澤潤, 齋藤翔太, 松嶋敏泰

    第40回情報理論とその応用シンポジウム予稿集  情報理論とその応用学会

    Presentation date： 2017.11

  • 正値の歪み超過確率を許容した可変長有歪み情報源符号化における符号語長のキュムラント母関数

    齋藤翔太, 松嶋敏泰

    第40回情報理論とその応用シンポジウム予稿集  情報理論とその応用学会

    Presentation date： 2017.11

  • ランク誤りを考慮したCoded Computation に関する一考察

    風間皐希, 鎌塚明, 松嶋敏泰

    第40回情報理論とその応用シンポジウム予稿集  情報理論とその応用学会

    Presentation date： 2017.11

  • 最小修復帯域幅を達成する再生成符号に基づく分散ストレージシステムにおける秘匿情報検索に関する一検討

    吉田隆弘, 松嶋敏泰

    第40回情報理論とその応用シンポジウム予稿集  情報理論とその応用学会

    Presentation date： 2017.11

  • 富士山型空間結合符号の重み分布に関する一考察

    中原悠太, 松嶋敏泰

    第40回情報理論とその応用シンポジウム予稿集  情報理論とその応用学会

    Presentation date： 2017.11

  • 統計的決定理論に基づく2次元ウェーブレットパケットを用いた画像修復

    小板橋和也, 中原悠太

    第2回WIRPワークショップ 

    Presentation date： 2017.04

  • 情報理論に基づく無歪み圧縮のための画像の数理モデル化に関する一考察

    中原悠太

    第2回WIRPワークショップ 

    Presentation date： 2017.04

  • A Note on New Schedule of BP Decoding Based on Local Cycle Distributions

    Nakahara, Yuta, Matsushima, Toshiyasu

    Presentation date： 2016.12

  • Variable-Length Lossy Compression Allowing Positive Overflow and Excess Distortion Probabilities

    Presentation date： 2016.12

  • 潜在変数を仮定した非線形回帰モデルおけるベイズ基準のもと最適な予測

    潮田 幹生, 鎌塚 明, 松嶋 敏泰

    第39回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 2016.11

  • 一般化された再生成符号に対する効率的な複数割当法による構成法

    鎌塚明, 吉田隆弘, 松嶋敏泰

    第39回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 2016.11

  • A Note on List Decoding of Codes over Symbol-Pair Read Channel

    Presentation date： 2016.11

  • 富士山型空間結合符号

    中原悠太

    第5回誤り訂正符号のワークショップ 

    Presentation date： 2016.09

  • On the Applications of Weibull Distribution with Nonstationary Scale Parameter

    Presentation date： 2016.03

  • A Note on a Privacy-Preserving Method for Distributed Regularized Logistic Regression

    Presentation date： 2016.01

  • A Note on Unequal Error Protection in Random Network Coding

    Presentation date： 2016.01

  • A Note on the Optimal Data Prediction under Bayes Criterion for Multidimensional Linear Regression Models Assuming Latent Variables

    Presentation date： 2016.01

  • A Study on Soft Decision Decoding for Array-Error Channel

    Presentation date： 2016.01

  • A Study on Message Passing Algorithm for Counting Short Cycles in Sparse Bipartite Graphs

    Presentation date： 2016.01

  • A Note on the Computational Complexity Reduction Method of the Optimal Prediction under Bayes Criterion in Semi-Supervised Learning

    Presentation date： 2016.01

  • A Note on the Linear Programming Decoding of Linear Codes for Symbol Pair Read Channel

    Presentation date： 2015.11

  • A Study of Regenerating Codes with Generalized Conditions of Reconstruction and Regeneration

    Presentation date： 2015.11

  • A Note on the Decoding of Polar codes using Search Algorithm

    Presentation date： 2015.11

  • 一般情報源に対するSmooth最大エントロピーを用いた可変長符号化の達成可能オーバーフローしきい値について

    第38回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 2015.11

  • On the Credible Interval Prediction of Web Traffic based on the Bayes Decision Theory

    Presentation date： 2015.11

  • On decoding of Polar codes using search algorithm

    Presentation date： 2015.09

  • Linear Programming Decoding of Binary Linear Codes over Symbol-Pair Read Channels

    Presentation date： 2015.09

  • Variations of the Strong Converse Theorem on the Intrinsic Randomness Problem for General Sources

    Presentation date： 2015.07

  • On the Bayes Optimal Prediction of Time Series under a Nonstationary Weibull Distribution

    Presentation date： 2015.07

  • Another Representation on the Second-Order Achievable Rate Region of Slepian-Wolf Coding Problem for General Sources

    Presentation date： 2015.03

  • A Note on the Linear Bandit Problem with Multiple Parameters

    Presentation date： 2014.12

  • プライバシー保護機能を持つ分散型正則化最小二乗法について

    第37回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 2014.12

  • Universality of Spatially Coupled Punctured LDPC Codes for Decode-and-Forward in Erasure Relay Channels

    Presentation date： 2014.12

  • Evaluation of the Minimum Overflow Threshold of Bayes Codes for Non-Stationary Sources

    Presentation date： 2014.12

  • A Note on the Effectiveness of Unlabeled Data for Prediction Error in Semi-Supervised Learning

    Presentation date： 2014.12

  • The Optimal Prediction under Bayes criterion for Linear Regression Models with Latent Variables

    Presentation date： 2014.12

  • Asymptotic Normality and LIL of the Codeword Length of Bayes Codes for Stationary Ergodic Markov Sources

    Presentation date： 2014.12

  • A Note on Attack Against Nonlinear Combiner Generator Using Sum - Product Algorithm

    Presentation date： 2014.11

  • A Note on Improvement in the Rate of a Prediction Error of AdaBoost in Pattern Recognition

    Presentation date： 2014.09

  • How to Observe Probability Distribution of Self-Information as viewed under different resolutions of $n^{-1}$ and $n^{-1/2}$

    Presentation date： 2014.07

  • A study of a MDP - based recommender system when the class of user who is recommended items is unknown

    Presentation date： 2014.07

  • A Note on Optimal Control System for Selective - Repeat Hybrid SR - ARQ with a Finite Length Buffer

    Presentation date： 2014.07

  • A Note on the Correlated Multiple Matrix Completion based on the Convex Optimization Method

    Presentation date： 2013.11

  • Asymptotics of Consistent Estimator - based Prediction for Semi-supervised Learning

    Presentation date： 2013.11

  • An Approximation of Bayes Prediction for Linear Regression Models

    Presentation date： 2013.11

  • Relationship Between the Overflow Probability of Variable-length Coding and the Error Probability of Fixed-length Coding

    Presentation date： 2013.11

  • Asymptotics of Bayesian Estimation for Hierarchical and Misspecied Models

    Presentation date： 2013.10

  • Evaluation of Minimum Overflow Threshold for Bayes Codes

    Presentation date： 2013.10

  • A Note on Construction of Parallel Concatenation Using Polar Codes

    Presentation date： 2013.10

  • A Consideration on the Storage and the Repair-bandwidth for Generalized Class of Regenerating Codes based on Leakage of Share

    Presentation date： 2013.10

  • Bayesian Prediction for Multivariate Polynomial Regression with Unknown Order

    Presentation date： 2013.10

  • Lossless Image Data Compression Based on Regression Trees

    Presentation date： 2013.10

  • An Approximation of Bayes Prediction for Linear Regression Models

    Presentation date： 2013.10

  • The Empirical Bayes Forecasting of Web Traffic on the Non-Stationary Poisson Distribution

    Presentation date： 2013.10

  • Iterative Multiuser Joint Decoding based on Augmented Lagrangian Method

    Presentation date： 2013.09

  • A Consideration on Modeling and Optimality of Regenerating Codes Considering Security of Shares

    Presentation date： 2013.07

  • プライバシー保護を目的とした線形回帰モデルにおける事後確率最大推定量の分散計算法について

    NAKAI Akito, SUKO Tota, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 2013.03

  • A Consideration on Minimum Storage Regenerating Codes for Functions

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. WBS, ワイドバンドシステム 

    Presentation date： 2013.03

  • プライバシー保護を目的とした線形回帰モデルにおける事後確率最大推定量の分散計算法について

    NAKAI Akito, SUKO Tota, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 2013.03

  • An Extended Privacy Preserving Regression Analysis

    Presentation date： 2012.12

  • A Note on Tree Model-Based Compressed Sensing Based on Augmented Lagrangian Method

    Presentation date： 2012.12

  • Linear Time ADMM Decoding for LDPC Codes over MIMO Channels

    Presentation date： 2012.12

  • A Privacy Preserving Distributed Calculation Method of Least-squares Estimator for Linear Regression Models

    Presentation date： 2012.11

  • An optimal prediction method using hierarchical N-gram based on Bayes decision theory

    Presentation date： 2012.09

  • Linear Programming Decoding for Multiple Access Channel based on Decomposition Methods

    Presentation date： 2012.09

  • Variable Order Transition Probability Markov Decision Process for the Recommendation System

    Presentation date： 2012.05

  • ベイズ決定理論にもとづく階層N グラムを用いた最適予測法と日本語入力支援技術への応用

    言語処理学会第18回年次大会（NLP2012）発表論文集 

    Presentation date： 2012.03

  • マルコフモデルによる自動分類に対する分類誤り確率の推定

    情報処理学会研究報告 

    Presentation date： 2012.03

  • Information Theory and Learning Theory

    Presentation date： 2012.03

  • Universal Markov Decision Process Designed by Bayes Decision Theory for the Recommendation System

    Presentation date： 2012.03

  • 実験計画法に適した直交配列の線形計画限界

    情報処理学会第74回全国大会 

    Presentation date： 2012.03

  • A Note on Analysing LDPC Codes for Correcting a Burst Erasure

    Presentation date： 2012.01

  • An Error Probability Analysis of the Text Classification Using the CTW Algorithm

    KOBAYASHI Manabu, GOTO Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会技術研究報告. NLP, 非線形問題 

    Presentation date： 2011.11

  • An Error Probability Analysis of the Text Classification Using the CTW Algorithm

    KOBAYASHI Manabu, GOTO Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会技術研究報告. NLP, 非線形問題 

    Presentation date： 2011.11

  • 次数が未知の状態遷移確率を仮定したマルコフ決定過

    第34回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 2011.11

  • A Study on Key Estimation of Stream Cipher based on Probabilistic Inference Algorithm

    Presentation date： 2011.07

  • A study of statistical modeling of authentication using PUF

    Presentation date： 2011.07

  • Asymptotics of Bayesian prediction for misspecified models

    Presentation date： 2011.07

  • A consideration on unconditionally secure key distribution schemes considering leakage of secret information of key distribution centers

    Presentation date： 2011.03

  • Lower bounds on the memory size of entities for a ramp key distribution scheme and an optimal construction

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. IT, 情報理論 

    Presentation date： 2011.01

  • Disk Allocation Methods for Cartesian Product Files by using Unequal Error Protection Codes

    SAITO Tomohiko, INAZUMI Hiroshige, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会技術研究報告. IT, 情報理論 

    Presentation date： 2011.01

  • Lower bounds on the memory size of entities for a ramp key distribution scheme and an optimal construction

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. IT, 情報理論 

    Presentation date： 2011.01

  • Disk Allocation Methods for Cartesian Product Files by using Unequal Error Protection Codes

    SAITO Tomohiko, INAZUMI Hiroshige, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会技術研究報告. IT, 情報理論 

    Presentation date： 2011.01

  • A Note on the Inference Algorithm on the Factor Graph based on the Linear Programming

    HORII Shunsuke, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会技術研究報告. IT, 情報理論 

    Presentation date： 2011.01

  • A Note on the Inference Algorithm on the Factor Graph based on the Linear Programming

    HORII Shunsuke, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会技術研究報告. IT, 情報理論 

    Presentation date： 2011.01

  • Maximum likelihood detection for DS-CDMA using Gr\{o}bner bases

    Presentation date： 2010.11

  • 複数の相関のある情報源に対するベイズ符号化について

    第33回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 2010.11

  • ,Achievable Condition in Resolvability Problem for Mixed Sources

    Presentation date： 2010.11

  • Linear Programming Decoding of Binary Linear Codes for Multiple-Access Channel

    HORII Shunsuke, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会技術研究報告. IT, 情報理論  (!) 

    Presentation date： 2010.09

  • Linear Programming Decoding of Binary Linear Codes for Multiple-Access Channel

    (!) 

    Presentation date： 2010.09

  • A Study on Key Estimation Attacks to Stream Cipher based on Statistical Decision Theory

    Presentation date： 2010.03

  • Universal Source Coding under an Unknown Alphabet

    Presentation date： 2009.12

  • A Note on Noiseless Separate Source Coding Theorems for Correlated Sources

    Presentation date： 2009.09

  • A Note on the Fixed-Length Source Coding Theorems for Sources with Side Information

    Presentation date： 2009.09

  • An Efficient Algorithm for the Bayes Codes using an Unlimited Depth Context Tree

    2008 SIP (IASTED Signal and Image Processing) 

    Presentation date： 2008.08

  • A Note on the Weak Universal Joint Source - Channel Coding

    Presentation date： 2008.01

  • A Note on Multiuser Detection Algorithms for CDMA based on the Belief Propagation Algorithm

    Presentation date： 2008.01

  • 開始と締切りが設定されたシステムの到着モデルとその応用

    オペレーションリサーチ学会 待ち行列研究部会 （招待講演） 

    Presentation date： 2007.11

  • On the Condition of epsilon-Achievable Overflow Thresholds for the Parametric Compound Sources

    Presentation date： 2007.05

  • Shortened and Concatenated Collusion-Secure Codes for Digital Fingerprinting

    Presentation date： 2007.05

  • A performance of the LZ78 code for Non-prefix-free Word-valued source

    Presentation date： 2007.01

  • Performance Analysis of EM Decoding Algorithm for HMM Channels

    Presentation date： 2006.11

  • A Note on the overflow probability of lossless codes

    Presentation date： 2006.11

  • Iterative decoding and detection techniques (invited talk)

    IEEE ITW06 

    Presentation date： 2006.10

  • On Error Exponents for Variable Size List decoder using the Viterbi Algorithm with Likelihood Ratio Testing

    Presentation date： 2005.11

  • Collusion-Secure Codes for Fingerprinting based on Finite Geometries

    Presentation date： 2005.11

  • A Study of Reliability Based Hybrid ARQ Schemes Using a Recursive Systematic Convolutional Code

    Presentation date： 2005.09

  • A Relation between Erasure Correcting and Error Correcting of Low-Density Parity-Check Codes

    Presentation date： 2005.09

  • インターネットトラヒックのポアソン分布の密度パラメータが時間変動する時系列モデルを用いた解析に関する一考察

    第4回情報科学技術フォーラム(FIT2005) 

    Presentation date： 2005.09

  • Matrix Clustering Method Achieving Specific Accuracy by Modified Apriori Algorithm

    Presentation date： 2005.06

  • A Note on Construction of Nonlinear Unequal Orthogonal Arrays from Error-Correcting Codes

    Presentation date： 2005.05

  • A Classification of the Probabilistic Reasoning given Distribution Evidence and Kullback-Leibler Information

    Presentation date： 2005.04

  • Universal Coding Algorithm for Side Information Context Tree Models

    Presentation date： 2004.12

  • Word segmentation of the sequences emitted from a word-valued source

    Presentation date： 2004.12

  • Universal Coding Algorithm for Side Information Context Tree Models

    第27回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2004.12

  • Bayes Universal Coding Algorithm for Side Information Context Tree Models

    Technical Program of the 4th Asia 

    Presentation date： 2004.08

  • Tailbiting 畳込み符号の復号アルゴリズムに関する一考察

    電子情報通信学会技術研究報告IT2004 

    Presentation date： 2004.07

  • ユニバーサル通信路符号化法における通信路容量について

    電子情報通信学会技術研究報告 

    Presentation date： 2004.03

  • A Note on Models of a Non-Prefix-Free Word-Valued Source

    Presentation date： 2003.12

  • 区間で一定なパラメータを持つ情報源におけるベイズ符号化法について

    第26回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2003.12

  • 衝突困難ハッシュ関数の安全性について

    第26回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2003.12

  • ベイズ決定理論に基づく予測における近似手法について

    第26回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2003.12

  • Parallel Propagation Algorithms for Tailbiting Convolutional Codes

    第26回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2003.12

  • 決定木モデルにおける予測アルゴリズムについて

    電子情報通信学会技術研究報告COMP2003 

    Presentation date： 2003.08

  • 相関のある時系列の状態空間によるモデル化と予測

    電子情報通信学会技術研究報告IT2003 

    Presentation date： 2003.07

  • 畳み込み符号の並列復号アルゴリズムの性能評価に関する一考察

    電子情報通信学会技術研究報告IT2003 

    Presentation date： 2003.07

  • ポアソン分布に従う非定常な時系列のモデル化に関する一考察

    電子情報通信学会技術研究報告IT2003 

    Presentation date： 2003.07

  • Generalized Posterior Probability and Its Calculation

    Technical Program of the 3rd Asia 

    Presentation date： 2003.06

  • Properties of a Word-valued Source with a Non-prefix-free Word Set

    Presentation date： 2003.05

  • 語頭条件を満たさない単語集合をもつWord-Valued Sourceの性質について

    電子情報通信学会技術報告IT2003 

    Presentation date： 2003.05

  • A Note on Robust Pattern Recognition based on Bayes Decision Theory

    Presentation date： 2002.12

  • Prediction Algorithm for Extended Hierarchical Models

    Presentation date： 2002.12

  • 単語単位で系列を出力する情報源の性質について

    第25回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2002.12

  • 誤り訂正符号を用いた直行計画の構成法に関する一考察

    第25回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2002.12

  • 拡張された階層モデルにおける予測アルゴリズムについて

    第25回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2002.12

  • リスト復号に対する判定帰還方式LR+THの誤り指数について

    第25回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2002.12

  • 一般化事後確率とその計算法

    電子情報通信学会技術研究報告IT2002 

    Presentation date： 2002.12

  • ベイズ決定理論に基づくロバストなパターン認識に関する一考察

    第25回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2002.12

  • 多端子情報源符号化に基づいた分散協調問題の定式化

    第25回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2002.12

  • Calculation of Generalized Posterior Distribution on Junction Graphs

    第25回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2002.12

  • On the Channel Capacity of Universal Channel Coding

    第25回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2002.12

  • ブール関数の逐次実験計画を用いた学習に関する一考察

    電子情報通信学会技術研究報告COMP2002 

    Presentation date： 2002.11

  • Computational Source Information Model and its Algorithm

    102 

    Presentation date： 2002.09

  • 「インターネットを用いたゼミと研究指導」実用化報告

    2002PCカンファレンス論文集 

    Presentation date： 2002.08

  • A study of calculating channel capacity for (2,2;2)-Multiple Access Channel

    Presentation date： 2002.07

  • 計算論的学習と情報圧縮に関する一考察

    電子情報通信学会技術研究報告IT2002 

    Presentation date： 2002.07

  • (2,2,2)-MACの通信路容量を求める手法に関する一考察

    電子情報通信学会技術研究報告IT2002 

    Presentation date： 2002.07

  • 低密度パリティチェック符号の復号アルゴリズムに関する一考察

    電子情報通信学会技術研究報告SST2001 

    Presentation date： 2002.03

  • ブロックターボ符号に対するインタリーバの構成法と最小距離

    第24回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2001.12

  • 多端子情報理論に基づく分散協調問題について

    第24回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2001.12

  • 「インターネットを用いた研究活動支援システム」システム構成と評価

    第13回日本経営工学会秋季大会 

    Presentation date： 2001.11

  • ベイズ決定理論による定式化のもとで直交計画を用いたブール関数の学習に関する一考察

    電子情報通信学会技術報告COMP2001 

    Presentation date： 2001.11

  • 形式言語と圧縮に関する一考察

    電子情報通信学会技術報告IT2001 

    Presentation date： 2001.11

  • 状態空間モデルを用いた時系列解析に関する一考察−モンテカルロフィルタにおけるサンプリング方法について−

    日本経営工学会秋季研究大会予稿集 

    Presentation date： 2001.11

  • ターボ符号，LDPC符号の復号アルゴリズム

    ベイジアンネットチュートリアル講演論文集 

    Presentation date： 2001.07

  • ブロックターボ符号の生成行列と性能評価

    電子情報通信学会技術研究報告IT2001 

    Presentation date： 2001.07

  • 多端子モデルに基づく分散協調問題の定式化について

    電子情報通信学会技術研究報告IT2001 

    Presentation date： 2001.07

  • パラメータが時間変化する情報源とその符号化に関する一考察

    電子情報通信学会技術研究報告IT2001 

    Presentation date： 2001.07

  • 微分幾何から見た確率推論と復号

    確率伝搬に基づく復号法と符号ワークショップ 

    Presentation date： 2001.03

  • ウェーブレット・パケットを用いた雑音除去におけるベイズ法の応用に関する一考察

    電子情報通信学会技術研究報告DSP2000 

    Presentation date： 2000.12

  • フーリエ変換を用いたブール関数の学習に関する一考察

    電子情報通信学会技術研究報告COMP2000 

    Presentation date： 2000.11

  • 不確実性を含む演繹推論に関する一考察

    第23回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2000.10

  • ユニバーサル符号における固定長符号の誤り率と可変長符号のオーバーフロー確率について

    第23回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2000.10

  • 尤度比検定を用いた木符号の復号法について

    第23回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2000.10

  • An Iterative Caluculation Algorithm for Posterior Probability

    第23回情報理論とその応用シンポジウム予稿集 

    Presentation date： 2000.10

  • Methematical Models in Information-Based Induction Science

    Presentation date： 2000.07

  • 確率推定誤差を考慮に入れた算術符号化アルゴリズム

    電子情報通信学会技術研究報告IT2000 

    Presentation date： 2000.07

  • 不確実な知識の演繹推論における二項述語への拡張に関する一考察

    人工知能学会全国大会（第14回）論文集 

    Presentation date： 2000.07

  • Ziv-Lempel符号の冗長度に関する一考察

    電子情報通信学会技術研究報告IT2000 

    Presentation date： 2000.07

  • 符号長の分散とオーバーフロー確率について

    第22回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1999.12

  • 不確実な知識の演繹推論アルゴリズムに関する一考察

    第22回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1999.12

  • 単語単位で系列を出力する情報源

    第22回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1999.12

  • 信頼度情報に基づく置換生成行列を用いた最尤復号法の効率化について

    第22回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1999.12

  • 質問からのブール関数の学習における学習戦略を求めるアルゴリズム

    第23回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1999.12

  • コスト付き情報源符号化定理について

    第22回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1999.12

  • Viterbi アルゴリズムを用いた判定帰還方式における再送要求によるリスタートとスループットについて

    第22回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1999.12

  • A Geometrical Interpretation on the Calculation of Posterior Probability and Turbo Decoding

    第23回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1999.12

  • Iterative Algorithms for Calculating Probability and Decoding

    Presentation date： 1999.09

  • 実用化せまるturbo符号・復号の理論と実際

    電気情報通信学会ソサイエティ大会 

    Presentation date： 1999.09

  • On the Error Probability of Model Selection for Classisfication

    1999 Workshop on Information-Based Induction Science 

    Presentation date： 1999.08

  • Compression and decoding of an inverted file by using syndrome

    Presentation date： 1999.07

  • CELP音声符号化方式のランダム駆動信号に関する一考察

    電子通信学会技術研究報告／電子情報通信学会 

    Presentation date： 1999.07

  • 誤り訂正符号の復号アルゴリズム

    電気情報通信学会総合大会 

    Presentation date： 1999.04

  • Soft-Decision Decoding Methods using Algebraic Decoding Algorithm

    Presentation date： 1999.03

  • 木符号におけるリスト復号法を用いた判定帰還方式について

    第21回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1998.12

  • 不確実性を伴う診断型エキスパートシステムのモデル化と推論法について

    第21回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1998.12

  • 不確実な知識の推論における欠測データの取り扱いに関する一考察

    第21回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1998.12

  • 適合フィードバックによる情報検索に関する一考察

    第21回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1998.12

  • 近似的なベイズ学習と学習可能性について

    第21回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1998.12

  • 音声認識における Hidden Markov Model のパラメータ推定に関する一考察

    第21回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1998.12

  • モデル族の部分集合に基づく予測方法について

    第21回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1998.12

  • Extended Stochastic Complexity の漸近式について

    第21回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1998.12

  • 帰納・演繹推論と予測−決定理論による学習モデル

    1998年情報論的学習理論ワークショップ予稿集／情報理論とその応用学会 

    Presentation date： 1998.07

  • The Generalization of Bayesian Network's Deductive Method

    信学技報／電子情報通信学会 

    Presentation date： 1998.07

  • 対数線形モデルを用いた不確実な知識の推論法について

    人工知能学会全国大会(第12回)論文集／人工知能学会 

    Presentation date： 1998.06

  • マルコフ決定過程の計算アルゴリズムについて

    人工知能学会全国大会(第12回)論文集／人工知能学会 

    Presentation date： 1998.06

  • On performance of prediction using side information

    Presentation date： 1998.05

  • 事後確率密度の漸近正規性

    平成10年度春季大会予稿集／日本経営工学会 

    Presentation date： 1998.05

  • 遺伝的アルゴリズムとK-means法を用いた非階層クラスタリング

    平成10年度春季大会予稿集／日本経営工学会 

    Presentation date： 1998.05

  • 階層モデル族のモデル選択における選択誤り率について

    信学技報／電子情報通信学会 

    Presentation date： 1998.01

  • Type for hierarchical probabilistic models

    Presentation date： 1997.12

  • A study of improving the Ziv - Lempel78 Code from the view point of Bayes Code

    Presentation date： 1997.12

  • 木構造型モデル族のモデル選択法に関する一考察

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • 不確実性を含むデータの統合に関する一考察

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • 直交表現された仮説の学習に関する一考察

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • 質問からの学習における予測誤りに関する一考察

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • 混合分布の近似とその性能について

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • 決定を考慮したベクトル量子化法の提案

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • 階層的確率モデルにおけるタイプについて

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • ベイズ符号化法におけるメモリの問題点に関する一考察

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • ベイズ符号の視点からのZiv-Lempel78符号の改良に関する一考察

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • BCH限界を超える復号アルゴリズムを用いたChase復号法の計算量低減

    第20回情報理論とその応用シンポジウム予稿集 

    Presentation date： 1997.12

  • On Decoding Method Beyond the BCH Bound

    Presentation date： 1997.07

  • 木構造モデル族の学習、予測アルゴリズムに関する一考察

    信学技報／電子情報通信学会 

    Presentation date： 1997.07

  • 不均一誤り訂正符号の復号法に関する一考察

    信学技報／電子情報通信学会 

    Presentation date： 1997.07

  • ベイズ統計学に基づく計算論的学習モデルと学習可能性

    信学技報／電子情報通信学会 

    Presentation date： 1997.07

  • ベイズ決定理論に基づく統計的モデル選択について

    信学技報／電子情報通信学会 

    Presentation date： 1997.07

  • トレリス符号を用いた有歪みデータ圧縮の一考察

    信学技報／電子情報通信学会 

    Presentation date： 1997.07

  • 統計的決定理論によるデータ検索の定式化と最適化

    人工知能学会全国大会(第11回)論文集／人工知能学会 

    Presentation date： 1997.06

  • 属性値の類似度を用いた概念学習の効率化

    春季大会予稿集／日本経営工学会 

    Presentation date： 1997.05

  • 属性のクラスタを用いた概念学習の効率化

    経営情報学会 

    Presentation date： 1997.05

  • ハッシュ技法によるデータ探索の数学的モデル化，及び探索効率の漸近的評価

    信学技報／電子情報通信学会 

    Presentation date： 1997.05

  • ClarkeとBarronのBayesian Asymptoticsについて

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 1997.01

  • A Study of An Automatic - Repeart - reQuest Strategy for Non-Stationary Channels

    Presentation date： 1996.12

  • On Soft-Decision Decoding using Error Correcting decoder Beyond the BCH Bound

    Presentation date： 1996.12

  • Codelength of Sufficient Statistic Code

    Presentation date： 1996.12

  • 異なる事前分布を持つ場合の MDL 原理に基づく符号とベイズ符号の符号長に関する一考察

    第19回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1996.12

  • On a Weight Structure for On-lineLearning and its Mistake Bound

    Presentation date： 1996.12

  • Machine Learning Ensembles of Hypotheses

    Presentation date： 1996.12

  • A Note on Variable to Fixed-Length Codes for Markov Sources

    Presentation date： 1996.12

  • A Study on Multiple-Input Signatusre Registers in LSI Self - Testing

    Presentation date： 1996.12

  • Bayes Coding for Data Compression

    Presentation date： 1996.12

  • A study of Ziv - Lempel Algorithm from the view point of Bayes Code

    Presentation date： 1996.07

  • On Complexity of Decoding Beyond the BCH Bound Using Berlekamp-Massey Algorithm : An Application for Soft-Decision Decoding Using Algebraic Decoder

    Presentation date： 1996.07

  • On Bayes Coding in the case of limited memories

    Presentation date： 1996.07

  • A Study on Error Probability of Statistical Model Selection

    Presentation date： 1996.07

  • A Note on Learning Uncertain Concept with Membership Queries

    Presentation date： 1996.06

  • An Algorithm Learning Probabilistic Rules

    Presentation date： 1996.06

  • An Analysis on Difference of the Codelengths between Codes Based on MDL Principle and Bayes Codes

    Presentation date： 1996.05

  • On coded AQR schemes cumulating the rejected sequences for very noisy channel

    Presentation date： 1996.05

  • LSI自己検査における並列シグネチャ解析器の構成

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 1996.04

  • 構成的帰納論理プログラミングに関する一考察

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 1996.02

  • 巡回符号の並列符号器・復号器に関する検討

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 1995.11

  • On Soft Decision Decoding for Reed-Solomon Codes

    Presentation date： 1995.10

  • On Reasoning Methods for Uncertain Knowledge from Noisy Examples

    Presentation date： 1995.10

  • On Universal Codes for FSMX Sources

    Presentation date： 1995.10

  • 矛盾を含む知識の取り扱いについての一考察

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • 不確実な知識の表現法と推論法について

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • 多重符号化を用いた判定帰還方式について

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • 選言的論理プログラムの効率的推論法について

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • 巡回符号の並列符号化器に関する検討

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • 質問を許す概念学習に関する一考察

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • 観測雑音を考慮した不確実な知識の推論法について

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • ユニバーサル情報源符号化アルゴリズムに基づく事後確率推定アルゴリズム

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • ベイズ決定理論に基づくデータ解析に関する一考察

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • Reed-Solomon符号の軟判定一復号法

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • On the Optimum Learning Algorithm for Boolean Functions and the Learnability based on Bayesian Statistics

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • FSMX情報源のユニヴァーサル符号について

    第18回情報理論とその応用シンポジウム予稿集/情報理論とその応用学会 

    Presentation date： 1995.10

  • A Note on Learning Theory for Probabilistic Models

    Presentation date： 1995.09

  • Note on Maximum Likelihood Decoding of Linear Block Codes

    Presentation date： 1995.07

  • A Study on Parameter Estimation and Ziv-Lempel Code

    Presentation date： 1995.07

  • 未知パラメータを含むマルコフ決定過程に関する一考察

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 1995.07

  • ベイズ符号を応用した疑似乱数の検定法

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 1995.07

  • ベイズ符号による情報源圧縮に関する一考察

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 1995.07

  • Optimum Learning Rules for Boolean functions based on Bayesian Statistics

    Presentation date： 1995

  • On the erasure option for the Viterbi algorithm and ARQ schemes

    Presentation date： 1994.12

  • A Two-Stage-Procedure for Universal Coding

    Presentation date： 1994.12

  • A Study on an Application of Neural Network to the {0,1} Classification Problem

    Presentation date： 1994.12

  • A Note on Update of Uncertain Knowledge

    Presentation date： 1994.07

  • A Note on the Construction Method of Decision Trees

    Presentation date： 1994.07

  • On the Complexity of Hypothesis Space and the Sample Complexity for Machine Learning

    Presentation date： 1994.07

  • Inductive and Deductive Inference based on Information Theory

    Presentation date： 1994.07

  • An Efficient Procedure of Inductive Learning for PROLOG

    Presentation date： 1994.06

  • An Inference from a Contradictory Knowledge

    Presentation date： 1994.06

  • 確信度と信頼率を用いた不確実な知識の表現と推論

    人工知能学会全国大会（第8回） 

    Presentation date： 1994.06

  • On coded ARQ schemes cumulating the rejected sequences

    Presentation date： 1994.05

  • On an ARQ using VA with cumulating the rejected sequences

    Presentation date： 1993.10

  • On a Machine Learning Model Based upon Decision Theory

    Presentation date： 1993.10

  • On block coded ARQ schemes cumulating the rejected information

    Presentation date： 1993.07

  • On Inductive Inference and Deductive Inference for Uncertain Knowledge from the view point of Information Theory

    Presentation date： 1992.09

  • Minmax Redundancy Distortionless Codes Constructed from A Class of Bayes Codes

    Presentation date： 1991.12

  • On decision criterion of decision feedback schemes

    Presentation date： 1991.12

  • Concept Learning via a finite number of Membership Queries

    Presentation date： 1991.12

  • On Study of Learning Algorithm for Monotone Conjunctions

    Presentation date： 1991.12

  • A Note on Hypothesis Selection in Hypothesis - based Reasoning

    Presentation date： 1991.01

  • An Inductive Inference Procedure to Minimize Prediction Error

    Presentation date： 1991.01

  • On decison feed - back scheme using Viterbi algorithm

    Presentation date： 1991.01

  • 有限系列に関する平均符号長を考慮したユニバーサル情報源符号化について

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 1991

  • A Study of Understanding Simile Using Sense Scales

    Presentation date： 1991.01

  • On a formulation of inference from the view point of information theoery and its application

    Presentation date： 1989.07

  • A Study on Realization of Universal Data Compression

    Presentation date： 1988.12

  • A Strategy on Feature Ordering and Stopping Rule with Maximizing Mutual Information

    Presentation date： 1987.11

  • Notes On the Decoding Time for Concatenated Codes

    Presentation date： 1987.11

  • ,On Algorithms with Information Measure for Production System Strategie

    Presentation date： 1987.11

  • A Stady of Discrete Data Analisis by Information Resolution

    Presentation date： 1986.10

  • A Study on Stopping Rules for Pattern Recognition

    Presentation date： 1986.10

  • 離散データの情報構造モデルに関する一考察

    電子情報通信学会技術研究報告/電子情報通信学会 

    Presentation date： 1986

  • A Consideration on Modeling and Optimality of Regenerating Codes Considering Security of Shares

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. IT, 情報理論 

  • Hierarchical Multi-label Classification on Statistical Decision Theory

    YAMAMOTO Kiyohito, SUKO Tota, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習 

  • A Privacy Preserving Distributed Calculation Method of Least-squares Estimator for Linear Regression Models

    SUKO Tota, HORII Shunsuke, KOBAYASHI Manabu, GOTO Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習 

  • Linear Programming Decoding for Multiple Access Channel based on Decomposition Methods

    HORII Shunsuke, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. IT, 情報理論 

  • Asymptotics of Bayesian prediction for misspecified models

    MIYA Nozomi, SUKO Tota, YASUDA Goki, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. IT, 情報理論 

  • A study of statistical modeling of authentication using PUF

    ISHII Satoru, YOSHIDA Takahiro, HORII Shunsuke, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. IT, 情報理論 

  • A Study on Key Estimation of Stream Cipher based on Probabilistic Inference Algorithm

    IIKUBO Yuji, HORII Shunsuke, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. IT, 情報理論 

  • A consideration on unconditionally secure key distribution schemes considering leakage of secret information of key distribution centers

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告. WBS, ワイドバンドシステム 

  • AK-2-4 Information Theory and Learning Theory

    MATSUSHIMA Toshiyasu

    電子情報通信学会総合大会講演論文集 

  • Berlekamo-Masseyアルゴリズムを用いたBCH限界を超える復号法の計算量について(共著)

    電子情報通信学会論文誌 

  • A Study of the Decision of Control Parameters for Adaptive Automatic-Repeat Request Strategy

    Electronics and Communications in Japan 

  • Fast Correlation Attackの改良法に関する一考察

  • ID情報に基づくランプ型分散鍵配送方式につい て

    第27回情報理論とその応用シンポジウム予稿集 

  • Small-Loopを含む低密度パリティ検査(LDPC)符 号の復号に関する研究

    第27回情報理論とその応用シンポジウム予稿集 

  • ランプ型鍵配送方式について

    電子情報通信学会技術報告 

  • 階層モデルにおけるベイズ予測の漸近評価に関する一考察

    第27回情報理論とその応用シンポジウム 

  • 外れ値データの発生を考慮にいれた回帰モデルにおけるベイズ予測法について

    2004年情報論的学習理論ワークショップ（IBIS2004）予稿集 

  • 確率推論とグラフ伝播復号アルゴリズム

    ベイジアンネットワークセミナー2004 

  • 確率推論とその周辺

    人工知能学会全国大会 

  • 区間で一定なパラメータを持つ非定常情報源におけるベイズ符号の冗長度について

    第27回情報理論とその応用シンポジウム予稿集 

  • 区間で定常なパラメータを持つ非定常情報源におけるベイズ符号の冗長度について

    電子情報通信学会技術報告IT2004-22 

  • 誤り訂正符号を利用した直交計画の構成法に関す る一考察 〜逐次実験に適した直交計画について〜

    第27回情報理論とその応用シ ンポジウム予稿集 

  • 質問学習と逐次実験計画の関係に関する一考察

    電子情報通信学会研究技術報告 AI2003-63 

  • 質問学習に直交計画を用いた場合の予測アルゴリズムに関する一考察

    人工知能基本問題研究会資料 SIG-FPAI-A402-12 

  • 電子透かしにおける秘匿容量計算計算アルゴリズム

    電子情報通信学会技術報告IT2005-94 

  • BW変換を用いたユニバーサル符号化アルゴリズムに関する研究

    第28回情報理論とその応用シンポジウム予稿集 

  • 帰還通信路を用いた誤り制御方式に関しての研究

    第28回情報理論とその応用シンポジウム予稿集 

  • A Note on HTTP Traffic Analysis of the Time Series Model with a Time Varying Density Parameter

  • 使用ユーザが変化するDS/CDMAシステムにおけるベイズ最適なマルチユーザ検出について

    第28回情報理論とその応用シンポジウム予稿集 

  • 単一ループをもつグラフィカルモデルにおける確率伝播型アルゴリズムに関する一考察

    第28回情報理論とその応用シンポジウム予稿集 

  • 再帰的畳み込み符号を利用したReliability Based Hybrid ARQについての研究

    電子情報通信学会技術研究報告IT2005-52 

  • FSMX情報源に対するベイズ符号のメモリ量削減アルゴリズム

    電子情報通信学会技術報告IT2005-47 

  • 電子透かしにおける秘匿容量の計算手法に関する研究

    電子情報通信学会技術報告 IT2005-47 

  • A Study of Reliability Based Hybrid ARQ Scheme with Bitwise Posterior Probability Evaluation from Message Passing Algorithm

  • A Note on Construction of Nonlinear Unequal Orthogonal Arrays from Error-Correcting Codes

  • インターネットを用いた研究支援環境〜電子会議システム〜

    経営情報学会2005年春季全国研究発表大会予稿集 

  • 統計的決定理論に基づく有限受信バッファSR ARQ方式

    第28回情報理論とその応用シンポジウム予稿集 

  • ID情報に基づくランプ型非対称鍵配送方式について

    暗号と情報セキュリティシンポジウム2006予稿集 

  • 統計的決定理論に基づく複数のクラスに属する文書の分類方法に関する一考察

    電子情報通信学会技術報告IT2005-89 

  • 相互通信可能なネットワーク上での情報伝送に関する一研究

    第29回情報理論とその応用シンポジウム予稿集 

  • On Factorial Effects Corresponding to Orthogonal Arrays with Unequal Strength

    Proceeding of 2006 Hawaii, IEICE and SITA Joint Conference on Information Theory 

  • A Note on Transmission Schemes with Unequal Error Protection Codes and a Feedback Channel

    Proc. of Society of Information Theory and its Applications (SITA2006) 

  • 未知パラメータを伴う隠れマルコフモデルの状態推定に関する一考察

    第29回情報理論とその応用シンポジウム予稿集 

  • A note on the epsilon-overflow probability of lossless codes

  • Multiuser Detection Algorithms for CDMA based on the Massage Passing Algorithms

  • Adaptive Increment Redundancy Coding and Decoding Schemes using Feedback Information

  • A Note on Transmission Schemes with Unequal Error Protection Codes and a Feedback Channel

    Proc. of Society of Information Theory and its Applications (SITA2006) 

  • 秘密情報を持つBroadcast Channel の Secrecy Capacity 計算アルゴリズム

    第29回情報理論とその応用シンポジウム予稿集 

  • 記憶のある通信路に適した誤り訂正符号の構成法に関する研究

    第29回情報理論とその応用シンポジウム予稿集 

  • 記号の出現パターンを考慮した情報源に対するベイズ符号に関する研究

    電子情報通信学会技術研究報告IT2006-29 

  • On Factorial Effects Corresponding to Orthogonal Arrays with Unequal Strength

  • The Reliability based Hybrid ARQ Scheme with both the Encoded Parity Bit Retransmissions and Message Passing Decoding

  • 直交計画と双対符号の関係に関する一考察

    電子情報通信学会研究技術報告 

  • ベイズ符号化アルゴリズムを用いたテキストデータ圧縮

    情報処理学会研究報告 

  • 変動要因を考慮した非定常ポアソンモデルに関する一考察

    電子情報通信学会技術研究報告 

  • ランプ型Robust 秘密分散法に関する一考察

    暗号と情報セキュリティシンポジウム2007予稿集 

  • 画像に対する状態表現を用いたモデル化と無歪み符号化

    第30回情報理論とその応用シンポジウム予稿集 

  • 盗聴・改ざんに対して耐性を持つネットワーク符号化について

    第30回情報理論とその応用シンポジウム予稿集 

  • 外れ値データの発生を含む回帰モデルに対するベイズ予測アルゴリズム

    情報処理学会研究報告 

  • 混合情報源に対するε達成可能なオーバーフローしきい値に関する考察

    第30回情報理論とその応用シンポジウム予稿集 

  • 差分一様性を利用したMACの改良について

    暗号と情報セキュリティシンポジウム, SCIS 2007 

  • New Bounds for PMAC, TMAC, and XCBC

    Fast Software Encryption, 14th International Workshop, FSE 2007, Luxembourg, Luxembourg, March 26-28, 2007, Revised Selected Papers. Lecture Notes in Computer Science 4593 Springer 2007 

  • Tweakable Enciphering Schemes from Hash-Sum-Expansion

    Progress in Cryptology - INDOCRYPT 2007, 8th International Conference on Cryptology in India, Chennai, India, December 9-13, 2007, Proceedings. Lecture Notes in Computer Science 4859 Springer 2007 

  • A Note on Morphological Analysis Methods based on Statistical Decision Theory

    SICE 2007 PROCEEDINGS 

  • スペルミスを伴う形態素解析に関する一考察

    第30回情報理論とその応用シンポジウム予稿集 

  • On the Condition of ε-achievable Overflow Thresholds for Mixed Sources

  • マーキング仮定に基づくフィンガープリンティング符号のキャパシティについて

    暗号と情報セキュリティシンポジウム2008（SCIS 2008） 

  • Efficient Domain Extension Using Weak Pseudorandom Function

    暗号と情報セキュリティシンポジウム, SCIS 2008 

  • A Note on the Weak Universal Joint Source-Channel Coding

  • 複数のLDPC符号の交錯による有限状態マルコフ通信路に適した誤り訂正符号の構成法について

    電子情報通信学会技術研究報告 

  • An Efficient Bayes Coding Algorithm using a New Unlimited Depth Context Tree

  • 実験計画法における効果の推定の計算量削減に関する一考察

    第31回情報理論とその応用シンポジウム予稿集 

  • A Note on Automatic Construction Algorithms for Orthogonal Designs of Experiments Using Error-Correcting Codes

    Pre-ICM International Convention on Mathematical Sciences 

  • An Accurate Density Evolution Analysis for a Finite-State Markov Channel

    Proc. of Society of Information Theory and its Applications (SITA2008) 

  • 区間で一定なパラメータを持つ非定常情報源の漸近的な性質について

    第31回情報理論とその応用シンポジウム予稿集 

  • ブロック誤り率が未知の場合の選択再送ARQに関する一考察

    第31回情報理論とその応用シンポジウム予稿集 

  • On the Overflow Probability of Lossless Codes for Mixed Sources

  • A Note on the Iterative Interference Cancellation and Decoding for Coded CDMA

  • A Linear Programming Bound for Unequal Error Protection Codes

  • 分枝カット法に基づいた線形符号の復号法に関する一考察

    第32回情報理論とその応用シンポジウム予稿集 

  • A Note on the Second Order Separate Source Coding Theorem for Sources with Side Information

  • Document Classification Method with Small Training Data

    ICCAS-SICE2009 

  • A Note on Theoretical Limit of Type-I Hybrid Selective-repeat ARQ with Finite Receiver Buffer

    ISCTA'09 

  • 通信路状態が未知の選択再送ARQに関する一考察

    第32回情報理論とその応用シンポジウム 

  • A Note on Fixed-Length Coding Theorem for Sources with Side Information

  • 相関のある情報源における符号化定理に関する一考察

    第7回シャノン理論ワークショップ予稿集 

  • A Note on Estimation of the Effects in the Experimental Design using Fourier Transforms

  • サービスの開始と終了を考慮したWebトラヒックの非定常Poisson過程によるモデル化について

    電子情報通信学会技術研究報告 

  • Applying Markov Decision Processes to Selective-repeat ARQ with Finite Receiver Buffer

    ISMAC2010 

  • Probabilistic World Logic for Modality of Uncertainty

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Research Projects

  • Construction of Bayesian Optimal Decision Tree Algorithm Using Metatree and Latent Class Tree by Information Theory

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2023.04
    -
    2027.03
     

  • ビジネス施策を正しく評価するための潜在構造に基づく協調フィルタリングに関する研究

    日本学術振興会  科学研究費助成事業

    Project Year :

    2023.04
    -
    2027.03
     

    小林 学, 平澤 茂一, 松嶋 敏泰

    　View Summary

    ビジネス施策を正しく評価するためには，種々のバイアスが含まれるデータから，その施策の効果を定量的に把握する必要がある．本研究では企業活動のデータを「顧客情報」「商品情報」「消費活動（顧客のアクション）」「ビジネス施策（企業のアクション）」の4種として表現し，その背後にある潜在構造を仮定した統一的なデータの生成観測メカニズムのフレームワークの提案を目指している．初年度は顧客と商品にそれぞれ潜在変数を仮定し，顧客情報，商品情報，消費行動およびビジネス施策と上の潜在変数との関係の数理構造を検討した．この時潜在変数間に階層構造を仮定することにより，上の様々な観測変数の複雑な関係を表現できることが分かった．また従来消費行動に量的変数を仮定していたが，消費行動が質的変数である場合の潜在構造とその推定アルゴリズムを提案し，有効性を示した．具体的には顧客と商品に対応する潜在変数を仮定する．次にこれらの潜在変数からそれぞれ顧客情報および商品情報が生成観測されるものとする．さらに顧客と商品の潜在変数同士の内積をとり，これにロジスティックシグモイド関数を適用することにより消費行動の質的変数が生成観測される潜在構造である．この時潜在変数と観測変数との関係にオリジナリティがあり，潜在構造の推定アルゴリズムは既存の統計的手法並びにモデル選択基準などを利用することが可能である．さらにこの潜在構造をうまく活用したモンテカルロEMによる繰り返し法を用いることにより，推定精度を上げることも可能であることを明らかにした．

  • 文系学生のためのAIプログラミング教育の最適化とオンライン教育システムの構築

    日本学術振興会  科学研究費助成事業

    Project Year :

    2022.04
    -
    2026.03
     

    浮田 善文, 斉藤 友彦, 松嶋 敏泰

    　View Summary

    本研究の目的は，文系学生のための一人一人に応じたAI教育のカリキュラム最適化と，多人数での学習を効率よく実施できるオンライン教育システムの構築を行うことである．令和5年度は，カリキュラム最適化に必要な情報を収集するために，研究代表者が所属している文系大学で開講している全科目と，高等学校での科目（情報，数学）の全単元について，内容の関連の調査を行い，以下の研究成果を得た．
    1. 公開されているシラバス情報を用いることで，大学科目と高校科目における単元間の類似度が容易に得られることを示した．また，この類似度を用いることにより，科目名だけでは気づきにくいものの類似度が高い科目を見つけられることが分かった．
    2. 選択した科目に対し，関連の強い大学科目および高校科目単元を視覚的に把握するための科目関連グラフを提案した．また，科目関連グラフは，大学で開講している全ての科目間のつながりを把握することが可能であるため，これまで知られていなかった異分野間の繋がりなどについても知ることができることを示した．
    3. 科目と単元間の類似度と，科目関連グラフを用いることで，授業担当者が少ない作業負担で，関連が強い大学科目および高校科目単元を把握可能であることを示した．さらに，関連の強い単元の情報を利用した，学生の授業理解度向上への取組についても考察を行った．

  • Research on Data Analysis Platform for Business Value Creation and Time-Varying Collaborative Filtering

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2019.04
    -
    2023.03
     

    Kobayashi Manabu

    　View Summary

    In this research, we constructed a platform (DAPF) that enables the analysis of proprietary big data held by companies in a secure environment on a server without exporting the data outside the server. The cloud DAPF effectively conducted practical operations in a total of five projects that analyzed real data. Furthermore, the on-premise DAPF verified scalability, such as multiple analysis environments using containers and external connections via VPN.
    Regarding collaborative filtering, we proposed a latent structure model that assumes multiple latent variables for various types of data, including customer and product attribute information, time information, and consumption behavior. This model integrates these data by considering the relationships between the observed and latent variables. We also evaluated the effectiveness of this model.

  • Programming Learning System by AI Coach

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2018.04
    -
    2021.03
     

    Saito Tomohiko

    　View Summary

    In this study, we developed various programming learning support systems using artificial intelligence and information communication technology, which have developed remarkably in recent years. The following two systems were developed and verified through this research. One is a web system for programming learning, and the other is a system for analyzing and estimating the level of understanding and concentration of learners who are learning programming. In addition, considering the social situation, we have added the development of an efficient learning system for distance learning as a new research topic in this study. In particular, we have developed a system to efficiently operate remote classes using Zoom and Meet, and a learning system using VR for future educational settings.

  • Fundamental research on finite length analysis in information theory and optimization theory for practical, reliable, and highly efficient communications

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2017.04
    -
    2021.03
     

    Matsushima Toshiyasu

    　View Summary

    In this research, we derived theoretical limits of performance of communication systems under practical conditions, such as when the codeword length is finite, and constructed a set of coding and decoding algorithm that achieve these theoretical limits. Theoretical limits such as code rate and error probability are precisely analyzed for practical communication channels, and in parallel, the entire coding and decoding system is formulated as a broad optimization problem to derive an optimal set of coding and decoding algorithm under more practical constraints. The results of theoretical limits in the practical condition were used as a heuristic function for optimization in the configuration of the coding and decoding system, and synergistic research such as validating global optimality and reduction of computational complexity in the coding and decoding algorithms was able to be promoted.

  • Creation of efficient simultaneous experiments for multiple objectives under Bayesian theory

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2017.04
    -
    2020.03
     

    UKITA Yoshifumi

    　View Summary

    In this study, we developed a framework that enables the processing of high-dimensional data, and proposed simultaneous experiments for multiple similar objectives that can examine all the factors to be considered in each objective. Since the model of experimental design can also be represented by an orthogonal basis function model in which all parameters are independent, we proposed a new method that uses both the traditional model and the orthogonal basis function model for programming when the number of factors and the dimensionality of parameters to be handled is very large, and clarified its characteristics.

  • Mathematical model and evaluation of efficiency and security for next-generation distributed storage systems with high-performance

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2016.04
    -
    2019.03
     

    YOSHIDA Takahiro

    　View Summary

    We have modeled a high-performance distributed storage system by extending and generalizing the mathematical model of the conventional distributed storage system. In addition, By defining the evaluation criteria of efficiency and security for our model, we have derived a trade-off between efficiency and security. As a result, it is possible to evaluate the performance of high performance distributed storage system considering both efficiency and security. Furthermore, we have presented a construction that optimizes efficiency while maintaining a certain security level

  • Construction of basic theory for next generation recommender system based on spatial analysis and temporal control

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2016.04
    -
    2019.03
     

    Maeda Yasunari

    　View Summary

    We apply Markov decision processes(MDP) to recommender system with transitions of user classes. A new recommender method which maximizes total reward is proposed under the condition that the true parameters of MDP are known. We also proposed a semi-supervised learning method for recommender system under the condition that the true parameters of MDP are unknown.We apply MDP to questionnaire for a new customer in recommender system. A new questionnaire method which maximizes the total reward is proposed under the condition that the true parameters of MDP are known. We also proposed a semi-supervised learning method for the new customer problem of recommender system under the condition that the true parameters of MDP are unknown

  • A Unified Analysis and Optimization of Information Security System with Probabilistic Components from Viewpoints of Convenience and Safety

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2013.04
    -
    2016.03
     

    MATSUSHIMA Toshiyasu, UKITA Yoshifumi, YOSHIDA Takahiro, NOMURA Ryo, SUKO Tota, HORII Shunsuke

    　View Summary

    Information security problem with probabilistic components has been formulated by probabilistic models. Theoretical criteria for evaluation such as convenience and safety have been defined clearly and optimal attack or an authentication method has been derived theoretically. Theoretical safety bounds have been evaluated with respect to mathematical models with unified framework for each cipher or security system. A theoretical safety bound or optimality has been clarified with respect to a tradeoff between convenience and safety. New theoretical criteria have been derived for information security systems. Approximation algorithms with high performance for optimal attack or an authentication method have been constructed applying results of studies on problems in related fields such as learning or optimization theory that is formulated by probabilistic models equivalent to our study. Convenience or safety of information security systems has been simulated by applying these algorithms

  • A Study on Unified Attack against Stream Ciphers based on Probabilistic Inference Algorithms

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2010
    -
    2012
     

    MATSUSHIMA Toshiyasu, UKITA Yoshihumi, NOMURA Ryo

    　View Summary

    Attack against Stream Cipher reduces to attack against a pseudo random generator. In this study, attack against a pseudo-random number generator was classified based on the choice of target variables and its order and the choice of the local relationships used for attack. We proposed efficient and accurate attack algorithms based on probabilistic inference by studying the problem in unified framework. We revealed the class of pseudo-random number generators that we can attack against based on the acquired knowledge of probabilistic inference so far.

  • Construction of Theory of Digital Analysis

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2008
    -
    2010
     

    YAMADA Yoshio, TAKAHASHI Daisuke, MATSUSHIMA Toshiyasu, KASHIWAGI Masahide, NISHIDA Takaaki, OISHI Shin'ichi

    　View Summary

    Our research group is composed of scholars working in the areas of discrete mathematics, nonlinear differential equations, information theory and numerical computation. We have organized "Seminar on Digital Analysis" so that members can hold common understanding and insight on the fundamental theories and ideas of digital mathematics. As speakers of this seminar, we have invited 16 researchers who are highly active in the areas of discrete mathematics, mathematical modeling, information theory and numerical computation. We have succeeded in getting common understanding on digital analysis through exciting discussions in each lecture of the seminar.

  • Modeling and optimization of the sensor networks based on the multiterminal information theory and decision theory

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2006
    -
    2008
     

    MATSUSHIMA Toshiyasu, SHIGEICHI Hirasawa

  • Application and Analysis of Parallel Iterative Algorithms for Calculating Posterior Probability to Practical Codes and Channels

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2003
    -
    2005
     

    MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    　View Summary

    For its good error correcting ability, Turbo code and Turbo decoding algorithm, which was proposed in the research area of the error correcting codes, have gotten a lot of attention recently as important technology of 21st century's reliable communication and accumulation technique. It have been known that the iterative decoding algorithms which includes Turbo decoding algorithm can be regarded as applications of Belief Propagation algorithm, which was proposed in the research area of the knowledge information processing as uncertain reasoning algorithm. It can be interpreted that the turbo decoding algorithm calculates the approximation of posterior probability effectively.It was obtained that the Extended Junction Graph (EJG) and the parallel iterative algorithm for calculating posterior probability, which are results achieved in "The Analysis and Design of the Reliable Iterative Decoding Algorithm based on Uncertain Reasoning" which is supported by Grant-in-Aid for Scientific Research in 2000-2002, can deal with general probabilistic models compared to existing belief propagation algorithm and retain the higher performance even when the graph has loops (almost of the practical codes have loops).In this research, we have done following,(1)We applied the EJG and the parallel iterative algorithm to the LDPC codes which have some small loops, we sought further efficiency and analyzed the performance.(2)We applied the algorithm to the channel models which have feedback channel such as ARQ Scheme and analyzed the performance.(3)Moreover, we applied the algorithm to the decryption of stream cipher and analyzed the performance

  • The Analysis and Design of the Reliable Iterative Decoding Algorithm based on Uncertain Reasoning

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    2000
    -
    2002
     

    MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    　View Summary

    1. We analyzed and generalized our original reasoning algorithm, which is already proposed, based on both Bayesian Network and Graphical Model. Then, we designed a new algorithm for calculating posterior probability on probability models including classes of efficient codes. We also inspected the algorithm in terms of both theoretical and simulating points and then got good results.2. Moreover, we inspected both convergence and accuracy of the algorithm in terms of the differential geometry, machine learning and statistics and then we gave theoretical understandings onto it.3. We defined the generalized posterior probability distribution and made mathematical expression of a problem of the uncertain reasoning given the observed probability distribution. It turned out that the result of our reasoning method has a lot of mathematical meanings that is very important. We improved our algorithm by reducing both the calculation and memory occupation, and by paralyzing its procedures.4. We applied our algorithm on the Extended Junction Graph, which is also our generalized original graph, then proposed the efficient parallel belief propagation algorithm. As a typical application, we applied our algorithm, which is already mentioned in 2., for decoding on Extended Junction Graph constructed by LDPC codes. We examined its natures in terms of both theoretical and experimental aspects.5. We used our Extended Junction Graph for both convolution codes and tail biting codes, then we applied our algorithm mentioned in 2. for decoding both codes. We examined its results from the both mathematical and computational points of view.6. We applied our generalized algorithm for calculating posterior probability, which is already proposed year 2001, to a special model class that has guarantee of convergence. The whole procedure guarantees mathematical meanings as well as both efficient calculation and memory occupation.7. We developed out results in year 2001 on decoding algorithm, then inspected from point of theoretical and experimental view

  • 環境共生型高精度エネルギー予測／高効率エネルギー利用技術

    文部科学省 

    Project Year :

    1998
    -
    2002
     

  • Application of coding techniques to multimedia

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research

    Project Year :

    1995
    -
    1997
     

    HIRASAWA Shigeichi, INAZUMI Hiroshige, TAJIMA Masato, NISHIJIMA Toshihisa, KOHNOSU Toshiyuki, MATSUSHIMA Toshiyasu

    　View Summary

    (1) (1)We studied data compression for text in source coding. We theoretically derived difference in code lengths between the codes based on the MDL principle and the Bays codes. Then these results were applied to the model selection problem.(2)We developed an approximately optimal algorithm which reduces complexity in calculation for the Bays code. We applied this algorithm to benchmark test, files, and so on, which gave good results. As data compression for speech, image, and so on, we also proposed an algorithm which applied the trellis codes to the source coding problem, and performed an evaluation experiment for this algorithm.(2) (1)In channel coding, we developed an algorithm on decoding beyond the BCH bound for BCH codes, and also an algorithm on soft decision decoding for block codes. From the viewpoint of complexity in calculation, we found a practical decoding method.(2)For convolutional codes, the relation between the Viterbi decoding method and the syndrome decoding method was elucidated. And these results were applied to the ARQ method. We found a decoding method having excellent performance at low rate.(3)We performed signature analysis by parallel processing as an application of the error-correcting codes to test methods of LSI

  • 経営工学における知識情報処理に関する研究

    日本学術振興会  科学研究費助成事業

    Project Year :

    1991
    -
    1993
     

    平澤 茂一, 松嶋 敏泰, 石渡 徳彌

    　View Summary

    近年,曖昧性や矛盾を含んだ知識の推論や学習等の,より人間的で複雑な判断をめざした新しい知識情報処理の基礎研究も様々な分野で盛んに行われている.しかしながら従来の論理学を中心としたエキスパートシステムに比べて基礎理論が不完全であり評価基準も不明確であるため得られる結果が理論的に明快に保証されずシステム化が進んでいないのが現状である.本研究ではこれら新しい知識情報処理のために今までの個別的な研究ではなく,人間や組織における判断で取り扱われる情報に着目した統一的な基礎理論の構築をめざしている.そして,その基礎理論上で個々の新しい知識情報処理の分野でネックとなっている基本問題について情報理論,統計理論的尺度から最適なアルゴリズムをいくつか提案し,さらにこのアルゴリズムを応用した知識情報システムの評価を行うことを目的とした.各研究者は主に以下の分担で研究を行った.研究代表者は主として情報の基本的性質に立脚し,情報理論及び符号理論を基本として情報の高信頼化,圧縮の基礎的研究を行うと共に分担研究者それぞれの情報にたいする視点をとりまとめ総合的に知識情報処理問題の考察を行った.研究分担者(石渡)は主として人間や組織における判断に必要となる情報やその判断の機構について基本的視点から考察すると共に,現在の意思決定システムの問題点及び将来像から打開しなければならない本質的問題を抽出し情報的視点から整理を行なった.研究分担者(松嶋)は主として従来型の知識情報処理の基礎理論である論理学だけでは取り扱えない新しい知識情報処理の問題点を整理し,情報理論,統計確率理論,決定理論など情報の基礎理論からの意味づけとモデル化を行った.さらに研究代表者と研究分担者がそれぞれ個別に研究を進めてきた情報に対する視点をまとめ,相互に意見交換することにより,現在及び将来の知識情報処理の基本問題を情報的視点より整理し,新しい基礎理論体系の枠組みの設定を行なった.また,この新しい基礎理論体系の枠組みをさらに洗練化させ,情報の視点から整理された新しい知識情報処理の為に重要ないくつかの基本的問題に対してこの基礎理論のモデルを適用する事により,いくつかの情報的視点から評価基準を設定し,そのもとで最適なアルゴリズムを提示した.また,経営工学やその周辺領域で今後必要となる将来型の知識情報システムにおける上記アルゴリズムの応用についての考察も行った

  • 情報理論を用いた帰納推論の基礎体系に関する研究

    日本学術振興会  科学研究費助成事業

    Project Year :

    1992
    　
    　
     

    松嶋 敏泰

▼display all

Misc

  • A Study on the Relationship Between Subject Similarity Based on Syllabus Information and the Correlation of Subject Grades in University Education

    浮田善文, 齋藤友彦, 松嶋敏泰

    情報科学技術フォーラム講演論文集   24th  2025

    J-GLOBAL

  • Bayes Optimal Decision on Infinite-Horizon MDPs with unknown latent variables of transition probability

    長船和也, 堀之内康平, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   124 ( 147(IT2024 14-25) )  2024

    J-GLOBAL

  • A Study on the Similarity of High School Subjects and College Subjects Using Educational Guidelines and Syllabus Information

    浮田善文, 齋藤友彦, 松嶋敏泰

    情報科学技術フォーラム講演論文集   23rd  2024

    J-GLOBAL

  • 特別講演

    松嶋 敏泰

    日本医科大学医学会雑誌   19 ( 4 ) 359 - 359  2023.12

    DOI

  • A Study on the Improvement of Course Comprehension Using the Similarity between Courses Based on Syllabus Information

    浮田善文, 齋藤友彦, 松嶋敏泰

    情報処理学会全国大会講演論文集   85th ( 4 )  2023

    J-GLOBAL

  • An Optimal Prediction on Multilevel Coefficient Linear Regression Model by Bayes Decision Theory and Its Approximation Method

    堀之内康平, 島田航志, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   122 ( 355(IT2022 29-67) )  2023

    J-GLOBAL

  • A Note on a New Method for Reducing Computation Time in Private Coded Computation

    三木淳司, GAO Shenzhe, 風間皐希, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   123 ( 14(IT2023 1-13) )  2023

    J-GLOBAL

  • An Extended Arimoto-Blahut Algorithm for Multiterminal Models and Its Convergence Property

    松嶋敏泰

    電子情報通信学会大会講演論文集(CD-ROM)   2023  2023

    J-GLOBAL

  • 潜在クラスに基づく混合線形回帰モデルを用いたUplift Modelingのベイズ最適な予測とその近似アルゴリズム

    飯窪祐二, 松嶋敏泰

    情報処理学会研究報告(Web)   2023 ( MPS-145 )  2023

    J-GLOBAL

  • A Note on Private Coded Computation Method with Tolerance Against Erasure of Responses from Server Groups

    森下雄介, 三木淳司, 風間皐希, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   123 ( 149(IT2023 14-29) )  2023

    J-GLOBAL

  • A Study on the Improvement of Course Comprehension Using the Similarity of Units in High School Courses and University Courses

    浮田善文, 齋藤友彦, 松嶋敏泰

    情報科学技術フォーラム講演論文集   22nd  2023

    J-GLOBAL

  • A New Framework for Multilevel Analysis Aiming at Optimal Prediction under Sparse Model Based on Bayesian Decision Theory

    堀之内康平, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   46th  2023

    J-GLOBAL

  • Two-Dimensional Auto-Regressive Models Whose Noise Variance Depends on Neighboring Pixels and Their Bayes Codes

    中原悠太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   46th  2023

    J-GLOBAL

  • Private Information Retrieval Using Secret Sharing Method and Extension for Robustness

    三木淳司, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   46th  2023

    J-GLOBAL

  • データサイエンスからみた生成AI問題

    松嶋敏泰, 松嶋敏泰

    日本医科大学医学会雑誌   19 ( 4 )  2023

    J-GLOBAL

  • A Note on Two-dimensional Autoregressive Model with Time-varying Parameters and the Bayes Codes

    中原悠太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   122 ( 25(IT2022 1-14) )  2022

    J-GLOBAL

  • A Note on a Group-type Distributed Coded Computation Scheme Based on a Gabidulin Code and its Erasure Decoding

    風間皐希, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   45th  2022

    J-GLOBAL

  • A Study on Accelerating Computation in Complex Space for Experiments Using Orthogonal Designs

    浮田善文, 齋藤友彦, 松嶋敏泰

    情報処理学会全国大会講演論文集   84th ( 1 )  2022

    J-GLOBAL

  • Bayes Optimal Approximation Algorithm by Boosting-like Construction of Meta-Tree Sets in Classification on Decision Tree Model

    馬庭良太, 一條尚希, 島田航志, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   122 ( 128(IT2022 15-28) )  2022

    J-GLOBAL

  • Meta-Tree Set Construction for Approximate Bayes Optimal Prediction on Decision Tree Model

    田島慶斗, 一條尚希, 島田航志, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   122 ( 128(IT2022 15-28) )  2022

    J-GLOBAL

  • An Efficient Algorithm for Optimal Decision on Piecewise Linear Regression Model by Bayes Decision Theory

    行谷昇, 島田航志, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   122 ( 128(IT2022 15-28) )  2022

    J-GLOBAL

  • A Study on Multilevel Coefficient Linear Regression Model and an Optimal Prediction for Multilevel Data by Bayes Decision Theory

    堀之内康平, 一條尚希, 石渡泰祐, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   122 ( 128(IT2022 15-28) )  2022

    J-GLOBAL

  • 開始終了間隔の回帰モデル化に基づく開始時点が異なる複数対象の単位期間内終了件数の予測

    香山渉, 中原悠太, 風間皐希, 島田航志, 小坂奏平, 藤田剛, 松嶋敏泰

    統計関連学会連合大会講演報告集   2022  2022

    J-GLOBAL

  • A Note on Boosting-like Construction of Meta-Tree Sets for Classification on Decision Tree Model

    馬庭良太, 一條尚希, 島田航志, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   45th  2022

    J-GLOBAL

  • A Note on Meta-Tree Set Construction for Approximate Bayes Optimal Prediction on Decision Tree Model

    田島慶斗, 一條尚希, 島田航志, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   45th  2022

    J-GLOBAL

  • Markov Chain Monte Carlo Method for Meta-Trees on Decision Tree Model

    中原悠太, 齋藤翔太, 一條尚希, 風間皐希, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   45th  2022

    J-GLOBAL

  • ベイズ決定理論に基づく機械学習ライブラリ:BayesML0.1.0

    中原悠太, 一條尚希, 島田航志, 飯窪祐二, 齋藤翔太, 風間皐希, 松嶋敏泰

    統計関連学会連合大会講演報告集   2022  2022

    J-GLOBAL

  • An Approximation by Meta-Tree Boosting Method to Bayesian Optimal Prediction for Decision Tree Model

    YU Wenbin, 風間皐希, 中原悠太, 一條尚希, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   121 ( 327(IT2021 28-82) )  2022

    J-GLOBAL

  • Bayes Optimal Estimation and Its Approximation Algorithm for the Difference with and without Measures for Population under the URL Model

    石渡泰祐, 齋藤翔太, 中原悠太, 飯窪祐二, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   44th  2021

    J-GLOBAL

  • Bayes Optimal Estimation and Its Approximation Algorithm for the Difference with and without Measures on New Sample under URL Model

    山田一翔, 中原悠太, 齋藤翔太, 飯窪祐二, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   44th  2021

    J-GLOBAL

  • 周辺画素によって異なる自己回帰係数を有する画像生成確率モデルとそのベイズ符号

    高野将大, 中原悠太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 320(IT2020 63-111) )  2021

    J-GLOBAL

  • An Efficient Bayes Coding Algorithm for the Source Based on Context Tree Models that Vary from Section to Section

    島田航志, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 410(IT2020 112-157) )  2021

    J-GLOBAL

  • An optimal prediction of phoneme under Bayes criterion by weighting multiple hidden Markov models

    山岡大志, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 397(EA2020 59-89) )  2021

    J-GLOBAL

  • A Note on the Reduction of Computational Complexity for Linear Regression Model Including Cluster Explanatory Variables and Regression Explanatory Variables; Bayes Optimal Prediction and Sub-Optimal Algorithm

    香山渉, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   121 ( 96(IT2021 15-27) )  2021

    J-GLOBAL

  • Bayesian Optimal Prediction and Its Approximation Algorithm for the Difference of Response Variables with and without Measures Considering Individual Differences by Assuming Latent Clusters.

    石渡泰祐, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   121 ( 96(IT2021 15-27) )  2021

    J-GLOBAL

  • The Optimal Denoising Algorithm under The Bayesian Criterion in case The Best 2D Discrete Wavelet Packets Basis Is Unknown

    岡凌平, 中原悠太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   44th  2021

    J-GLOBAL

  • 回帰木のベイズ的アプローチに基づくGAM/GA2M

    小林学, 松嶋敏泰, 平澤茂一

    日本経営工学会春季大会予稿集(Web)   2021  2021

    J-GLOBAL

  • サンプリングの偏りを考慮したデータ生成確率モデルの提案

    山田一翔, 鎌塚明, 中原悠太, 松嶋敏泰

    日本経営工学会春季大会予稿集(Web)   2021  2021

    J-GLOBAL

  • Markov Decision Processes for Simultaneous Control of Multiple Objects with Different State Transition Probabilities in Each Cluster

    本村勇人, 鎌塚明, 風間皐希, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 395(IBISML2020 34-61) )  2021

    J-GLOBAL

  • A Note on Secure Distributed Matrix Multiplication Methods Based on Secret Sharing Systems with General Access Structures

    風間皐希, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   44th  2021

    J-GLOBAL

  • 高効率なプライバシー保護情報検索システムの構成アルゴリズムの提案

    今津潮, 風間皐希, 松嶋敏泰

    日本経営工学会春季大会予稿集(Web)   2021  2021

    J-GLOBAL

  • A Coded Computation Method Based on a Gabidulin Code and the Evaluation of its Error-Correcting Capability

    風間皐希, 鎌塚明, 吉田隆弘, 松嶋敏泰

    電子情報通信学会論文誌 A(Web)   J104-A ( 6 )  2021

    J-GLOBAL

  • AI Human Resources Education：Data Science Education Program at Waseda University

      62 ( 1 ) e27 - e32  2020.12

    DOI CiNii

  • データサイエンスをどう捉えてどう教えるか : 早稲田大学での取り組みを交えながら—特集 データサイエンス教育の潮流(その1)

    松嶋 敏泰

    オペレーションズ・リサーチ = Communications of the Operations Research Society of Japan : 経営の科学   65 ( 10 ) 544 - 550  2020.10

    CiNii J-GLOBAL

  • Private Information RetrievalとSmooth Locally Decodable Codesの対応関係に関する一考察—A Note on the Relationship between Smooth Locally Decodable Codes and Private Information Retrieval—情報セキュリティ

    風間 皐希, 鎌塚 明, 吉田 隆弘, 松嶋 敏泰

    電子情報通信学会技術研究報告 = IEICE technical report : 信学技報   119 ( 474 ) 201 - 206  2020.03

    CiNii

  • A Note on Optimality of Orthogonal Designs in Complex Space

    Yoshifumi Ukita, Toshiyasu Matsushima

      1 ( 1 ) 171 - 172  2020.03

    J-GLOBAL

  • A Note on the Relationship between Smooth Locally Decodable Codes and Private Information Retrieval

    風間皐希, 鎌塚明, 吉田隆弘, 松嶋敏泰

    電子情報通信学会技術研究報告   119 ( 473(IT2019 90-120) )  2020

    J-GLOBAL

  • A Statistical Decision-Theoretic Approach for Measuring Privacy Risk in Information Disclosure Problem

    宮下有咲, 鎌塚明, 吉田隆弘, 松嶋敏泰

    電子情報通信学会技術研究報告   119 ( 473(IT2019 90-120) )  2020

    J-GLOBAL

  • Asymptotic Evaluation of α-divergence between VB Posterior Predictive Distribution and Bayesian Predictive Distribution

    山田一翔, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 105(IT2020 11-17) )  2020

    J-GLOBAL

  • Bayes Optimal Detecting Relevant Changes for i.p.i.d. Sources

    鈴木海理, 鎌塚明, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 42(EMM2020 1-10) )  2020

    J-GLOBAL

  • An Autoregressive Image Generative Model and the Bayes Code for It

    中原悠太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 42(EMM2020 1-10) )  2020

    J-GLOBAL

  • Construction of Hidden Marcov Models for Brain Tumor Segmentation

    本多拓哉, 中原悠太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 38(SIP2020 1-16) )  2020

    J-GLOBAL

  • 複数の対象が複数のクラスタに属するマルコフ決定過程における同時制御手法の提案

    本村勇人, 鎌塚明, 松嶋敏泰

    統計関連学会連合大会講演報告集   2020  2020

    J-GLOBAL

  • ニューラルネットワークの深層化の利点の理論解析:回帰関数の表現力と勾配法の学習効率を区別した評価基準

    江崎泰志, 中原悠太, 松嶋敏泰

    統計関連学会連合大会講演報告集   2020  2020

    J-GLOBAL

  • 線形回帰モデルの混合の統一的なフレームワークにおけるベイズ最適な予測とその近似アルゴリズム

    村山春香, 齋藤翔太, 飯窪祐二, 中原悠太, 松嶋敏泰

    統計関連学会連合大会講演報告集   2020  2020

    J-GLOBAL

  • Policy Optimization Based on Bayesian Decision Theory in Learning Period on Markov Decision Process

    一條尚希, 中原悠太, 本村勇人, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 268(IT2020 24-62) )  2020

    J-GLOBAL

  • Approximation Method for Bayes Optimal Prediction in Phoneme Recognition Problem

    山岡大志, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 268(IT2020 24-62) )  2020

    J-GLOBAL

  • フォーラム 早稲田大学におけるデータサイエンス人材育成への取り組み

    Ouyou toukeigaku   49 ( 1 ) 21 - 25  2020

    DOI CiNii J-GLOBAL

  • Performance Limit of Classification in the Presence of Label Noise with Erasure

    安田豪毅, 須子統太, 小林学, 松嶋敏泰

    電子情報通信学会技術研究報告(Web)   120 ( 268(IT2020 24-62) )  2020

    J-GLOBAL

  • A Note on the Relationship between Smooth Locally Decodable Codes and Private Information Retrieval

    風間皐希, 鎌塚明, 吉田隆弘, 松嶋敏泰

    電子情報通信学会技術研究報告   119 ( 473(IT2019 90-120) )  2020

    J-GLOBAL

  • A Study on Simultaneous Experiments for Related Linear Models based on an Orthonormal System

    Yoshifumi Ukita, Toshiyasu Matsushima

    Bayes on the Beach 2019    2019.11  [Refereed]

  • Gradient Coding based on LDGM Codes and Stochastic Gradient Descent

    堀井俊佑, 吉田隆弘, 小林学, 松嶋敏泰

    電子情報通信学会技術研究報告   119 ( 47(IT2019 1-14) )  2019

    J-GLOBAL

  • Optimal Estimating the Number of Change Points for Sources with Piecewise Constant Parameters under Bayesian Criterion

    鈴木海理, 鎌塚明, 松嶋敏泰

    電子情報通信学会技術研究報告   119 ( 89(IBISML2019 1-17)(Web) )  2019

    J-GLOBAL

  • Bayes Optimal Classification on Decision Tree Model and Its Approximative Algorithm Using Ensemble Learning

    土橋那央, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告   119 ( 149(IT2019 15-25) )  2019

    J-GLOBAL

  • Bayes Optimal Prediction and Its Approximative Algorithm on Model Including Cluster Explanatory Variables and Regression Explanatory Variables

    村山春香, 齋藤翔太, 中原悠太, 松嶋敏泰

    電子情報通信学会技術研究報告   119 ( 149(IT2019 15-25) )  2019

    J-GLOBAL

  • ラベルノイズの下での分類に関する性能の限界について

    安田豪毅, 須子統太, 小林学, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   42nd  2019

    J-GLOBAL

  • セキュアな再生成符号に基づく分散ストレージシステムにおける秘匿情報検索

    鎌塚明, 風間皐希, 吉田隆弘, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   42nd  2019

    J-GLOBAL

  • Bayesian Independent Component Analysis under Hierarchical Model on Latent Variables

    浅葉海, 齋藤翔太, 堀井俊佑, 松嶋敏泰

    電子情報通信学会技術研究報告   117 ( 475(IBISML2017 90-104) )  2018

    J-GLOBAL

  • Evaluation of Bayes Predictive Distributions under Unknown Parametric Models on Misspecified Models

    河野浩和, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告   117 ( 489(WBS2017 84-133) )  2018

    J-GLOBAL

  • Asymptotic Evaluation of Classification in the Presence of Generalized Label Noise

    安田豪毅, 須子統太, 小林学, 松嶋敏泰

    電子情報通信学会技術研究報告   118 ( 284(IBISML2018 44-104)(Web) )  2018

    J-GLOBAL

  • メロディの生成数理モデルを仮定した自動作曲

    西川史織, 中原悠太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   41st  2018

    J-GLOBAL

  • 富士山型空間結合符号に対するCovariance Evolution

    中原悠太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   41st  2018

    J-GLOBAL

  • 攻撃者の目的と背景知識を明確にしたプライバシ保護を考慮した情報公開

    宮下有咲, 鎌塚明, 吉田隆弘, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   41st  2018

    J-GLOBAL

  • 早稲田大学におけるデータ科学教育の取り組み ~早稲田大学データ科学総合研究教育センターの活動~

    須子統太, 小林学, 堀井俊佑, 安田豪毅, 松嶋敏泰

    日本経営工学会秋季大会予稿集(Web)   2018  2018

    J-GLOBAL

  • 拡張直交配列を利用した多水準の実験計画法に関する一考察

    山口純輝, 風間皐希, 鎌塚明, 齋藤翔太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   41st  2018

    J-GLOBAL

  • (n,k,d,r,t,x,y)qLRC符号の最小距離および次元の限界式に関する一考察

    風間皐希, 鎌塚明, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   41st  2018

    J-GLOBAL

  • Variable-Length Intrinsic Randomness Problem Allowing Non-Vanishing Underflow Probability

    吉澤潤, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告   117 ( 120(IT2017 16-37) )  2017

    J-GLOBAL

  • 陽に記述された画像生成モデルに対するベイズ基準のもと最適な可逆符号化

    中原悠太, 松嶋敏泰

    映像情報メディア学会冬季大会講演予稿集(CD-ROM)   2017  2017

    J-GLOBAL

  • 富士山型空間結合符号の重み分布に関する一考察

    中原悠太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   40th  2017

    J-GLOBAL

  • 最小修復帯域幅を達成する再生成符号に基づく分散ストレージシステムにおける秘匿情報検索に関する一検討

    吉田隆弘, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   40th  2017

    J-GLOBAL

  • 正値の変動距離を許容した可変長intrinsic randomness問題

    吉澤潤, 齋藤翔太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   40th  2017

    J-GLOBAL

  • 正値の歪み超過確率を許容した可変長有歪み情報源符号化における符号語長のキュムラント母関数

    齋藤翔太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   40th  2017

    J-GLOBAL

  • ランク誤りを考慮したcoded computationに関する一考察

    風間皐希, 鎌塚明, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   40th  2017

    J-GLOBAL

  • Reed-Solomon Code and Its Decoding Method

      70 ( 4 ) 571 - 575  2016.07

    CiNii

  • A Note on Support Recovery of Sparse Signals using Belief Propagation

    堀井俊佑, 松嶋敏泰, 平澤茂一

    電子情報通信学会技術研究報告   116 ( 33 ) 19 - 24  2016.05

    CiNii J-GLOBAL

  • A Consideration on Relationships between Correlation of Information Stored on Nodes and Coding Efficiency for Cooperative Regenerating Codes

    吉田隆弘, 松嶋敏泰

    電子情報通信学会技術研究報告   116 ( 33 ) 25 - 30  2016.05

    CiNii J-GLOBAL

  • A Note on a Privacy-Preserving Method for Distributed Regularized Logistic Regression

    増井秀之, 宮希望, 松嶋敏泰

    電子情報通信学会技術研究報告   115 ( 414 ) 281 - 286  2016.01

    CiNii J-GLOBAL

  • A Study on Message Passing Algorithm for Counting Short Cycles in Sparse Bipartite Graphs

    中原悠太, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告   115 ( 394 ) 13 - 18  2016.01

    CiNii J-GLOBAL

  • A Note on the Optimal Data Prediction under Bayes Criterion for Multidimensional Linear Regression Models Assuming Latent Variables

    潮田幹生, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告   115 ( 414(PRMU2015 115-131) )  2016

    J-GLOBAL

  • A Note on the Computational Complexity Reduction Method of the Optimal Prediction under Bayes Criterion in Semi-Supervised Learning

    中野雄斗, 齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告   115 ( 414(PRMU2015 115-131) )  2016

    J-GLOBAL

  • BP復号における局所サイクル分布に基づく復号順序制御に関する一考察

    中原悠太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   39th  2016

    J-GLOBAL

  • 一般化された再生成符号に対する効率的な複数割当法による構成法

    鎌塚明, 吉田隆弘, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   39th  2016

    J-GLOBAL

  • 潜在変数を仮定した非線形回帰モデルおけるベイズ基準のもと最適な予測

    潮田幹生, 鎌塚明, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   39th  2016

    J-GLOBAL

  • A Study on Soft Decision Decoding for Array-Error Channel

    風間皐希, 鎌塚明, 松嶋敏泰

    電子情報通信学会技術研究報告   115 ( 394(IT2015 48-100) )  2016

    J-GLOBAL

  • シンボルペア通信路における符号のリスト復号に関する一考察

    風間皐希, 鎌塚明, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   39th  2016

    J-GLOBAL

  • On decoding of Polar codes using search algorithm

    鎌塚明, 松嶋敏泰

    電子情報通信学会技術研究報告   115 ( 214 ) 55 - 60  2015.09

    CiNii J-GLOBAL

  • Linear Programming Decoding of Binary Linear Codes over Symbol-Pair Read Channels

    堀井俊佑, 松嶋敏泰, 平澤茂一

    電子情報通信学会技術研究報告   115 ( 214 ) 1 - 6  2015.09

    CiNii J-GLOBAL

  • Variations of the Strong Converse Theorem on the Intrinsic Randomness Problem for General Sources

    齋藤翔太, 松嶋敏泰

    電子情報通信学会技術研究報告   115 ( 137 ) 1 - 6  2015.07

    CiNii J-GLOBAL

  • Another Representation on the Second-Order Achievable Rate Region of Slepian-Wolf Coding Problem for General Sources

    SAITO Shota, MIYA Nozomi, MATSUSHIMA Toshiyasu

    Technical report of IEICE. ISEC   114 ( 471 ) 159 - 165  2015.03

    　View Summary

    In this paper, we deal with the Slepian-Wolf coding problem for general sources. Previously, the first-order ε-achievable rate region is derived for general sources by Han using information spectrum methods. Moreover, this result is extended to the second-order achievable rate region by Nomura et al. On the other hand, the first-order ε-achievable rate region is derived for general sources by Uyematsu et al. using different approach from information spectrum methods. In this research, we extend this result to the second-order achievable rate region. Furthermore, we show the relationship between our result and the rate region defined by the smooth max-entropy and the conditional smooth max-entropy.

    CiNii J-GLOBAL

  • 一般情報源に対するSmooth最大エントロピーを用いた可変長符号化の達成可能オーバーフローしきい値について

    齋藤翔太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   38th  2015

    J-GLOBAL

  • シンボルペア通信路における線形符号の線形計画復号法に関する一考察

    堀井俊佑, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   38th  2015

    J-GLOBAL

  • Polar符号の探索アルゴリズムを用いた復号法に関する一考察

    鎌塚明, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   38th  2015

    J-GLOBAL

  • 復元および再生成の条件を一般化した再生成符号に関する一考察

    東優太, 鎌塚明, 吉田隆弘, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   38th  2015

    J-GLOBAL

  • Special Section on Information Theory and Its Applications FOREWORD

    Toshiyasu Matsushima

    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES   E97A ( 12 ) 2287 - 2287  2014.12

    Other  

  • A Note on Attack Against Nonlinear Combiner Generator Using Sum-Product Algorithm

    KUBO Kota, SAITO Shota, KAMATSUKA Akira, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告   114 ( 306 ) 357 - 364  2014.11

    　View Summary

    When parameters have some restrictions, we can present it on a graphical model and find the values of unknown parameters from the parameters that we know. The one method to estimate the values of unknown parameters is to apply Sum-Product Algorithm(SPA). This technique is also discussed in cryptology. In this paper, finding the value of unknown parameters in stream cipher by using SPA is discussed. Some loops exist in the graph, thus the result of SPA is not guaranteed. Therefore, we evaluate calculating posterior probabilities using SPA by changing shape of the graphical model, and by changing message passing schedule.

    CiNii J-GLOBAL

  • How to Observe Probability Distribution of Self-Information as viewed under different resolutions of n^<-1> and n^<-1/2>

    MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   114 ( 138 ) 83 - 88  2014.07

    　View Summary

    Several problems in Information Theory are investigated by asymptotic approximations of the probability of self-information or self-mutual information. Two kind of normal asymptotic approximation is discussed in this paper. One is the approximation of tail distribution, and the other is the approximation of top distribution that is the neighborhood of the mode in the distribution. Error probability and overflow probability are evaluated by the approximation of tail distribution. Mean code length and point wise code word length are evaluated by the approximation of top distribution.

    CiNii J-GLOBAL

  • A study of a MDP-based recommender system when the class of user who is recommended items is unknown

    IWAI Shusuke, MIYA Nozomi, MAEDA Yasunari, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   114 ( 138 ) 49 - 54  2014.07

    　View Summary

    Recommender system is a system that gives users objects, information and items they want. In previous studies, recommendation was once and result of recommendation was not considered. Recently, in contrast, studies that consider results of recommendation have done. For example, there are studies that apply marcov decision process to recommender system. In addition, there are studies that apply marcov decision process and statistical decision theory to recommender system. These studies consider all users' probability of purchase are same. In contrast, we consider users are belongs to a class that classified by similarity. In addition, we consider the probability of purchase by users belongs to the class is different from the probability of purchase by users belongs to other class. We consider classes of users whose purchase data we have are known and class of the user who is recommended item is unknown. Then, we use marcov decision process and statistical decision theory. We renovate decision function by maximizing bayes criterion when the user who is recommended items buy new item.

    CiNii J-GLOBAL

  • A Note on Optimal Control System for Selective-Repeat Hybrid SR-ARQ with a Finite Length Buffer

    KAGEYAMA Yuta, KAMATSUKA Akira, MAEDA Yasunari, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   114 ( 138 ) 55 - 58  2014.07

    　View Summary

    Hybrid ARQ is one of the error correction scheme. It is Combination of ARQ and FEC. Algorithms for throughput maximization were proposed. But their efficiency was not guaranteed in theory. In this study, A way of acknowledgement decision is formulated by Markov decision process in terms of statical decision theory. The algorithm of throughput maximization which is considered reliablity is derived.

    CiNii J-GLOBAL

  • 消失中継通信路上でのDecode-and-Forward型通信におけるパンクチャされた空間結合LDPC符号のユニバーサル性

    中原悠太, 齋藤翔太, 鎌塚明, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   37th  2014

    J-GLOBAL

  • 潜在変数によって表現された線形回帰モデルにおけるベイズ基準の下で最適な予測

    都築遼馬, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   37th  2014

    J-GLOBAL

  • 半教師付き学習における予測誤差に対するラベルなしデータの有効性に関する一考察

    大和田歩, 安田豪毅, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   37th  2014

    J-GLOBAL

  • 定常エルゴードマルコフ情報源に対するBayes符号の符号語長の漸近正規性と重複対数の法則

    齋藤翔太, 宮希望, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   37th  2014

    J-GLOBAL

  • 非定常情報源に対するBayes符号のオーバーフロー確率における最小しきい値の評価

    守屋貴司, 齋藤翔太, 宮希望, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   37th  2014

    J-GLOBAL

  • パラメータが複数存在するLinear Banditに関する一考察

    堀井俊佑, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   37th  2014

    J-GLOBAL

  • Iterative Multiuser Joint Decoding based on Augmented Lagrangian Method

    HORII Shunsuke, SUKO Tota, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   113 ( 228 ) 13 - 17  2013.09

    　View Summary

    In this paper, we develop an iterative multiuser joint decoding of code-division multiple-access (CDMA) signals based on a distributed optimization algorithm. For the joint decoding problem, decoding algorithm based on the turbo principle is widely used. The algorithm consists of soft-input soft-output (SISO) channel decoder and SISO multiuser detector and it can be derived as an application of the sum-product algorithm. On the other hand, in the research area of error correcting codes, the decoding algorithm based on convex optimization has been attracting a great deal of attention. Decoding algorithm based on linear programming (LP) has decoding error rate which is comparable with sum-product algorithm with stronger theoretical guarantees. We formulate the joint decoding problem of CDMA signals as an convex optimization problem and we present a relax form of the problem. Moreover, we propose a distributed algorithm which efficiently solves the relaxed optimization problem. The proposed algorithm is based on alternating direction method of multipliers (ADMM).We also see the performance of the proposed decoder through numerical simulations.

    CiNii

  • A Consideration on Modeling and Optimality of Regenerating Codes Considering Security of Shares

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   113 ( 153 ) 27 - 32  2013.07

    　View Summary

    We consider regenerating codes. Regenerating codes are a class of codes for distributed storage systems that enable a data collector to recover the original data by connecting to any k of n storage nodes, and also can repair a failed node by downloading data from any d (≧=k) nodes. In regenerating codes, there exists a tradeoff between the storage size of each node and repair-bandwidth. In this study, we define two classes of regenerating codes considering security of each node's share, and show that the regenerating codes, which was proposed by Rashmi, Shah and Kumar, achieve the minimum storage size and repair-bandwidth for our class of regenerating codes.

    CiNii J-GLOBAL

  • A Consideration on Minimum Storage Regenerating Codes for Functions

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    Technical report of IEICE. ISEC   112 ( 461 ) 107 - 112  2013.03

    　View Summary

    We consider regenerating codes for functions. Regenerating codes are a class of codes for distributed storage systems that enable a data collector to recover the original data by connecting to any k of n storage nodes, and also can repair a failed node by downloading data from any d(≧k)nodes. In this study, we present explicit construction of regenerating codes for function (p(.)that enable a data collector to compute (p(x)for input J by connecting to any k;nodes and sending J to all connected nodes. The presented codes can repair a failed node by downloading data from any d (≧k)nodes as with regenerating codes, and achieve the minimum storage capacity.

    CiNii J-GLOBAL

  • Hierarchical Multi-label Classification on Statistical Decision Theory

    YAMAMOTO Kiyohito, SUKO Tota, MATSUSHIMA Toshiyasu

    電子情報通信学会技術研究報告   112 ( 452 ) 101 - 106  2013.03

    　View Summary

    This paper considers multi-label classification on statistical decision theory. In Label Power Set format, multi-label classification is equivalent to multi-class classification. However, the number of classes increases exponentially as elements in label set grow in number. Hence in case of many labels, a prohibitive computational cost problem occurs. To avoid this problem, some studies have been done and one of them used hierarchical structure. On the other hand, optimal classification method based on bayes rule has been attracted much attention recently. We apply this optimal classification method based on bayes rule to multi-label classification problem. Moreover, assuming hierarchical structure on labels, we propose efficient classification algorithms which reduce computational cost to linear order on the number of elements in label set. Since optimal classification based on bayes rule differs calculation formula depending loss function, we present algorithms in case of O-1 loss and hamming loss, respectively.

    CiNii J-GLOBAL

  • プライバシー保護を目的とした線形回帰モデルにおける事後確率最大推定量の分散計算法について (情報論的学習理論と機械学習)

    中井 祥人, 須子 統太, 松嶋 敏泰

    電子情報通信学会技術研究報告 : 信学技報   112 ( 452 ) 47 - 54  2013.03

    　View Summary

    本稿では,プライバシー保護を目的とした回帰分析について扱う.従来では,2者が異なる属性に関する説明変数を保持している場合,それぞれの保持するデータを互いに知らせることなく,2者間で協力し回帰係数の最小二乗推定量を求めるプロトコルが提案されている.しかし,事後確率最大推定量を求める分散計算法については研究が行われていない.そこで本研究では,さらに第三者の協力を得ることで,回帰係数のMAP推定量を求める分散計算プロトコルを提案する.そのもとで,提案プロトコルの安全性について評価を行う.また,事前分布の一部の共分散をOとおくと,提案プロトコルは簡単なものとなることを示す.そして,データ保持者が3者以上の場合への拡張も行う.

    CiNii J-GLOBAL

  • ベイズ符号のオーバーフロー確率における最小しきい値の評価

    齋藤翔太, 宮希望, 野村亮, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   36th  2013

    J-GLOBAL

  • 真の分布を含むとは限らない階層モデル族に対するベイズ推定の漸近評価

    宮希望, 須子統太, 安田豪毅, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   36th  2013

    J-GLOBAL

  • Polar符号を用いた並列連接符号化に関する一考察

    鎌塚明, 堀井俊佑, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   36th  2013

    J-GLOBAL

  • 線形回帰モデルにおけるベイズ決定理論に基づく予測の近似手法

    都築遼馬, 須子統太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   36th  2013

    J-GLOBAL

  • 回帰木を用いた画像の無歪みデータ圧縮

    小林学, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   36th  2013

    J-GLOBAL

  • 凸最適化に基づいた相関のある複数行列の同時補完に関する一考察

    堀井俊佑, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   36th  2013

    J-GLOBAL

  • 半教師付き学習における一致推定量に基づく予測の漸近評価

    安田豪毅, 宮希望, 須子統太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   36th  2013

    J-GLOBAL

  • 分散情報の情報漏洩量に基づく一般的な再生成符号のクラスに対するストレージと修復バンドワイズに関する一検討

    吉田隆弘, 地主創, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   36th  2013

    J-GLOBAL

  • 次数未知の多変数多項式回帰モデルにおけるベイズ予測

    山本粋士, 須子統太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   36th  2013

    J-GLOBAL

  • A Privacy Preserving Distributed Calculation Method of Least-squares Estimator for Linear Regression Models

    SUKO Tota, HORII Shunsuke, KOBAYASHI Manabu, GOTO Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    電子情報通信学会技術研究報告   112 ( 279 ) 107 - 111  2012.10

    　View Summary

    In this paper, we study a privacy preserving linear regression analysis. We propose a new protocol of distributed calculation method that calculates a least squares estimator, in case that two parties have different types of explanatory variables. We show security of privacy in the proposed protocol. Because the protocol have iterative calculation, we evaluate the number of iterations with numerical experiments. Finally, we show an extended protocol that is a distributed calculation method for κ parties.

    CiNii J-GLOBAL

  • Linear Programming Decoding for Multiple Access Channel based on Decomposition Methods

    HORII Shunsuke, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   112 ( 215 ) 53 - 58  2012.09

    　View Summary

    In this paper, we develop a dual decomposition method based linear-programming (LP) decoding for multiple-access channels with binary linear codes. LP decoding has decoding error rate which is comparable with state-of-the-art Sum-Product decoder for the decoding problem of binary linear codes with stronger theoretical guarantees and it is applied to decoding problems over various channels such as interference channels and multiple-access channels. But the decoder has to solve an LP problem and in general its computational complexity is the polynomial order of the number of variables and the number of constraints. Therefore it needs more decoding time compared to other decoders such as Sum-Product decoder. In order to tackle the complexity problem, many complexity efficient decoders have been developed for single-user memoryless channels. Especially, some previous studies showed that the decoding algorithm based on dual decomposition works well for large scale LDPC codes. In this paper, we apply the dual decomposition methods for the decoding problem over multiple access channels.

    CiNii

  • マルコフモデルによる自動分類に対する分類誤り確率の推定

    小林学, 後藤正幸, 松嶋敏泰, 平澤茂一

    全国大会講演論文集   2012 ( 1 ) 61 - 63  2012.03

    　View Summary

    カテゴリが既知の学習データを用いて,新規データのカテゴリを推定する自動分類問題は,サポートベクターマシンなど数多く研究が行われている.本研究では,カテゴリ中に発生するデータがマルコフモデルに従って発生すると仮定したときに,学習データを用いて分類誤り確率を推定する手法を提案する.

    CiNii J-GLOBAL

  • 実験計画法に適した直交配列の線形計画限界

    斉藤 友彦, 浮田 善文, 松嶋 敏泰, 平澤 茂一

    情報処理学会第74回全国大会   74th ( 1 ) 261 - 262  2012.03

    J-GLOBAL

  • Universal Markov Decision Process Designed by Bayes Decision Theory for the Recommendation System

    桑田修平, 桑田修平, 前田康成, 松嶋敏泰, 平澤茂一

    情報処理学会研究報告(CD-ROM)   2011 ( 6 )  2012

    J-GLOBAL

  • Variable Order Transition Probability Markov Decision Process for the Recommendation System

    桑田修平, 桑田修平, 前田康成, 松嶋敏泰, 平澤茂一

    情報処理学会研究報告(CD-ROM)   2012 ( 1 )  2012

    J-GLOBAL

  • MIMO通信路に対するLDPC符号の線形時間ADMM復号

    小林学, 堀井俊佑, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   35th  2012

    J-GLOBAL

  • プライバシー保護を目的とした回帰分析の拡張について

    須子統太, 堀井俊佑, 小林学, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   35th  2012

    J-GLOBAL

  • 木構造を仮定した信号に対する拡張ラグランジュ法に基づいた圧縮センシングについて

    堀井俊佑, 須子統太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   35th  2012

    J-GLOBAL

  • An optimal prediction method using hierarchical N-gram based on Bayes decision theory

    末永高志, 末永高志, 松嶋敏泰

    情報処理学会研究報告(CD-ROM)   2012 ( 3 )  2012

    J-GLOBAL

  • ベイズ決定理論にもとづく階層Nグラムを用いた最適予測法と日本語入力支援技術への応用

    末永高志, 松嶋敏泰

    言語処理学会年次大会発表論文集   18th (CD-ROM)  2012

    J-GLOBAL

  • An Error Probability Analysis of the Text Classification Using the CTW Algorithm

    KOBAYASHI Manabu, GOTO Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Nonlinear problems   111 ( 276 ) 109 - 114  2011.11

    　View Summary

    The text classification problem has been investigated by various techniques, such as a vector space model, a support vector machine, and so on. On the other hand, the Context-Tree Weighting (CTW) algorithm has been proposed as an outstanding data compression. Furthermore, experimental results have been reported using the CTW algorithm for the text classification. In this paper, we assume that each document with same category arises from one stochastic model for the text classification using the CTW algorithm. Then we propose an analysis method to obtain the classification error probability for the document with the finite length.

    CiNii J-GLOBAL

  • A Study on Key Estimation of Stream Cipher based on Probabilistic Inference Algorithm

    IIKUBO Yuji, HORII Shunsuke, MATSUSHIMA Toshiyasu

    IEICE technical report   111 ( 142 ) 7 - 12  2011.07

    　View Summary

    The stream cipher which is a kind of symmetric key algorithm, is a cryptosystem to generate ciphertext by XOR plaintext bits and keystream bits which obtained by input a secret key to pseudorandom number generator. In this paper, we formularize the problem of the attack to stream cipher by statisitical decision theory, and consider the optimal key estimation based on Bayesian criterion. We represent practical pseudorandom number generator as a probabilistic model, and propose the key estimation algorithm based on probabilistic inference one by representing it to graphical model. The proposed algorithm is evaluated by simulation, then consider the safety of the stream cipher.

    CiNii J-GLOBAL

  • A study of statistical modeling of authentication using PUF

    ISHII Satoru, YOSHIDA Takahiro, HORII Shunsuke, MATSUSHIMA Toshiyasu

    IEICE technical report   111 ( 142 ) 19 - 24  2011.07

    　View Summary

    Nowadays, it is pointed out that storing the secret in nonvolatile memory of the device has a chance to leak the secret because of physical attacks and side channel attacks. In order to solve this, Physical Unclonable Functions(PUF) were proposed. Recently, many encryption methods using PUF have been proposed, and one of typical example is authentication. In this paper, we define response to challenge of PUF as probability distribution, and we define error rate of authentication and success rate of impersonation attack by interpreting authentication using PUF as hypothesis testing problem. In authentication using PUP, we derive lower bound of success rate of impersonation attack when error rate of authentication is 0. And we define arbiter PUF which is one of silicon PUFs as probability distribution. In arbiter PUP, we simulate lower bound of success rate of the impersonation attack when error rate of authentication is 0, and discuss security of arbiter PUF.

    CiNii J-GLOBAL

  • Asymptotics of Bayesian prediction for misspecified models

    MIYA Nozomi, SUKO Tota, YASUDA Goki, MATSUSHIMA Toshiyasu

    IEICE technical report   111 ( 142 ) 71 - 76  2011.07

    　View Summary

    We consider the sequential prediction problem which is the prediction of the next symbol based on the sequential observation of source symbols. The log loss function in this problem is classified into two types, the instantaneous loss and the cumulative loss. The former is the loss function for the prediction of the only next one symbol. The latter is the sum of the instantaneous loss. We consider the Bayesian prediction for this problem. In Bayesian prediction, it is assumed that the true model lies within a parametrized family of distributions. However, it can be considered that it lies without a parametrized family practically(misspecified models), the true model being unknown. We analyze asymptotics of the cumulative loss for Bayesian prediction under this situation.

    CiNii J-GLOBAL

  • AK-2-4 Information Theory and Learning Theory

    MATSUSHIMA Toshiyasu

    Proceedings of the IEICE General Conference   2011   "SS - 17"-"SS-20"  2011.02

    CiNii J-GLOBAL

  • A consideration on unconditionally secure key distribution schemes considering leakage of secret information of key distribution centers

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    IEICE technical report   110 ( 443 ) 289 - 294  2011.02

    　View Summary

    A key distribution scheme (KDS) is a method of distributing secret keys in the network. In the conventional KDS, the security model was defined for collision attack by using the available information of centers and users. In this study, we define a KDS based on a new security model considering leakage of secret information of key distribution centers as well as collusion of centers and users. In our definition of KDS, we derive lower bounds on memory sizes and amount of received information of each entity, and show the concrete construction that meets corresponding lower bounds.

    CiNii J-GLOBAL

  • Disk Allocation Methods for Cartesian Product Files by using Unequal Error Protection Codes

    SAITO Tomohiko, INAZUMI Hiroshige, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report   110 ( 363 ) 7 - 12  2011.01

    　View Summary

    Allocation methods for Cartesian product files on multiple disks by using linear error-correcting codes were proposed. In this paper, we propose an allocation method using unequal error protection(UEP) codes. Code-words of an UEP code have some special bits which are protected against a greater number of errors than other bits. We firstly assume a model that "*", which means "don't care". appear with different probability in each attribute of queries. In this case, the average response time can be calculated by using the split distance distribution. Then, we calculate the average response time of the allocation method using UEP codes, and we show the effectiveness of this method from numerical examples.

    CiNii J-GLOBAL

  • A Note on the Inference Algorithm on the Factor Graph based on the Linear Programming

    HORII Shunsuke, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report   110 ( 363 ) 55 - 60  2011.01

    　View Summary

    Probabilisitc inference problem on the graphical model is very important since it is arising in many applications which include theory of error-correcting codes, image processing, speech recognition, and so on. Recently, linear programming based decoding algorithm for the error-correcting code has been receiving a lot of attention. Viewing the decoding problem as an example of the probabilistic inference problem on the graphical model, the factor graph corresponds to the problem has some specific structure. The functions in the factor graph can be classified into two classes, indicator functions and non-indicator functions. For the graph corresponds to the decoding problem, each non-indicator function is connected to only one variable node. On the other hand, the factor graph corresponds to the general probabilistic inference problems possibly have non-indicator functions which is connected to more than one variable nodes. The aim of this study is to develop the linear programming based inference algorithm for general inference problems.

    CiNii J-GLOBAL

  • Lower bounds on the memory size of entities for a ramp key distribution scheme and an optimal construction

    YOSHIDA Takahiro, JINUSHI Hajime, MATSUSHIMA Toshiyasu

    IEICE technical report   110 ( 363 ) 19 - 24  2011.01

    　View Summary

    The security notion of conventional ramp key distribution scheme (KDS) is that fraudulent centers and users can get partial information on any key that leak in stages according to the number of fraudulent users. In this paper, we define a new ramp KDS, show lower bounds on the memory size of entities for a new ramp KDS, and describe the concrete construction that meets corresponding lower bounds. The security notion of a new ramp KDS is that fraudulent centers and users can get partial information on any key that leak in stages according to the number of fraudulent centers and users.

    CiNii J-GLOBAL

  • 次数が未知の状態遷移確率を仮定したマルコフ決定過程

    桑田修平, 桑田修平, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   34th  2011

    J-GLOBAL

  • 物理的特徴を用いた認証方式の統計的モデル化と安全性評価に関する一検討

    吉田隆弘, 地主創, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   34th  2011

    J-GLOBAL

  • Linear Programming Decoding of Binary Linear Codes for Multiple-Access Channel

    HORII Shunsuke, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   110 ( 205 ) 31 - 36  2010.09

    　View Summary

    In this paper, we develop a linear-programming (LP) decoding for the multiple-access channel with binary linear codes. For the single-user channel, LP decoding has been attracting much attention in recent years as a good approximation to the maximum likelihood decoding. We demonstrate that how the maximum likelihood decoding problem for the multiple-access channel with binary linear codes can be formulated as a linear programming problem. It is not straightforward because the objective function of the problem is a non-linear function of the codeword symbols in general. We introduce the auxiliary variables such that the objective function is a linear function of those variables. Then the ML decoding problem reduces to the LP problem however, it is too complex for practical implementation. As the case for the single-user channel, we formulate the relaxed LP problem. Just as in the case of the single-user channel, the proposed decoder has the desirable property called ML certificate property, that is, if the decoder outputs integer solution, it is guaranteed to be the ML codeword. The computational complexity of the proposed algorithm is the exponential order of the number of users, however, we can reduce the computational complexity of the algorithm for the gaussian multiple-access channel. Furthermore, we compare the performance of the proposed decoder with the decoder based on the sum-product algorithm.

    CiNii

  • A-4-4 A Note on Estimation of the Effects in the Experimental Design using Fourier Transforms

    UKITA Yoshifumi, MATSUSHIMA Toshiyasu

    Proceedings of the Society Conference of IEICE   2010   73 - 73  2010.08

    CiNii

  • A Study on Key Estimation Attacks to Stream Cipher based on Statistical Decision Theory

    YUDIASTICHA Ety, MINEMATSU Kazuhiko, MATSUSHIMA Toshiyasu

    IEICE technical report   109 ( 446 ) 281 - 287  2010.02

    　View Summary

    This study looks at stream cipher that use nonlinear combination generator's output, which has multi-LFSR and a nonlinear function as generator's component, as random sequence for encryption and decryption. Key estimation attack is a kind of attack to this stream cipher which estimate a secret key employ given random sequence. Study on previous key estimation attacks have variety way on valuation method that makes difficult to have an unified valuation of stream cipher system's safeness. This study reformulates key estimation attack to this stream cipher problem based on statistical decision theory. Under reformulation, this study develops the expression for most appropriate key estimation attack based on Bayesian standard that can be an unified valuation standard of stream cipher's safeness. Furthermore, consider the position of previous attack algorithm from most appropriate key estimation attack's point of view.

    CiNii J-GLOBAL

  • 複数の相関のある情報源に対するベイズ符号化について

    須子統太, 堀井俊佑, 松嶋敏泰, 平澤茂一, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   33rd  2010

    J-GLOBAL

  • A Note on Analysing LDPC Codes for Correcting a Burst Erasure

    HOSOYA Gou, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report   109 ( 357 ) 7 - 10  2009.12

    　View Summary

    A lower bound on a probability of a burst erasure correction capability of regular low-density parity-check (LDPC) code ensemble under the belief-propagation decoding is investigated. This bound is based on the second moment method which expresses the upper bound on the minimum span for stopping sets of the regular LDPC code ensemble.

    CiNii

  • A Note on the Fixed-Length Source Coding Theorems for Sources with Side Information

    NOMURA Ryo, MATSUSHIMA Toshiyasu

    IEICE technical report   109 ( 212 ) 31 - 36  2009.09

    　View Summary

    The source coding theorem reveals the minimum achievable code length under the condition that the error probability is smaller than or equal to some small constant. In the single user communication system, the source coding theorem was proved for general sources. The class of general source is quite large and it is important result since the result can be applied for a wide class of sources. On the other hand there is a study to evaluate the achievable code length more precisely for the restricted class of sources by using the restriction. In the multi-user communication system, although the source coding theorem was proved for general correlated sources, there is no study to evaluate the achievable code length more precisly. In this study, we consider the problem that there exists a side information. This setting is one kind of correlated sources and show the coding theorem more precisely than the previous result.

    CiNii J-GLOBAL

  • A Modeling and Evaluation of Sensor Network based on Multiterminal Information Theory

    NOMURA RYO, MATSUSHIMA TOSHIYASU

      2009 ( 9 ) 1 - 8  2009.09

    CiNii

  • 学習データが少量の場合の文書分類方法

    前田康成, 吉田秀樹, 藤原祥隆, 松嶋敏泰

    電気学会全国大会講演論文集   2009 ( 3 )  2009

    J-GLOBAL

  • 早稲田大学全学共通副専攻「データ解析」コースの取組みについて

    石田崇, 瀧澤武信, 松嶋敏泰

    PC Conference論文集   2009  2009

    J-GLOBAL

  • 符号化率が適応的に可変で確定的に構成したパンクチャドLDPC符号の性能

    細谷剛, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   32nd  2009

    J-GLOBAL

  • 通信路状態が未知の選択再送ARQに関する一考察

    前田康成, 吉田秀樹, 鈴木正清, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   32nd  2009

    J-GLOBAL

  • 分枝カット法に基づいた線形符号の復号法に関する一考察

    堀井俊佑, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   32nd  2009

    J-GLOBAL

  • 実験計画法における効果の推定の計算量削減に関する一考察

    浮田 善文, 松嶋 敏泰, 平澤 茂一

    第31回情報理論とその応用シンポジウム予稿集   31st   945 - 950  2008.10

    J-GLOBAL

  • Error Correcting Codes using plural LDPC codes and Interleaving for a Finite-State Markov Channel

    KOBAYASHI Naoto, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report   108 ( 202 ) 55 - 60  2008.09

    　View Summary

    In this paper, we study interleaved codes with plural LDPC codes. Interleaved codes are one of efficient error correcting schemes for burst errors. Interleaver is utilized for utilized to disperse burst error. In contrast, interleaver is utilized for good estimation of the channel states for joint estimation-decoding in this study. We evaluate error correcting performance of the interleaved codes by computer simulation. Furthermore, we propose a simple analysis method for this interleaved codes based on density evolution method considered to the states of channels.

    CiNii J-GLOBAL

  • A Note on the Weak Universal Joint Source-Channel Coding

    NOMURA Ryo, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report   107 ( 422 ) 1 - 6  2008.01

    　View Summary

    In this paper, a weak universal joint source-channel coding is considered. Weak universal means that a source probabilistic structure and a channel probabilistic structure are parametric and the set of parameter and its prior probability are known, but the parameter is unknown. Then we show a condition for the class of sources and channels that the error probability averaged by prior probability converges to 0.

    CiNii

  • ソリッドバースト消失の訂正に適した非正則LDPC符号の構成について

    細谷剛, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   31st  2008

    J-GLOBAL

  • ブロック誤り率が未知の場合の選択再送ARQに関する一考察

    前田康成, 吉田秀樹, 藤原祥隆, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   31st  2008

    J-GLOBAL

  • 区間で一定なパラメータを持つ非定常情報源の漸近的な性質について

    須子統太, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   31st  2008

    J-GLOBAL

  • A Bayes Prediction Algorithm for Regression models with Outliers

    SUKO Tota, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IPSJ SIG Notes   2007 ( 128 ) 13 - 16  2007.12

    　View Summary

    Outliers are often included in statistical data. The statistics analysis result is influenced from outliers. Therefore, there are many researches for handling of outliers. Box modeled outliers using mixture distribution. There are many researches that aim parameter estimation or outlier detection about this model. In this paper, we treat prediction problem about this model. First, we present an optimal prediction method with reference to the Bayes criterion in this model. The computational complexity of this method grows exponentially. Next, we propose an approximation algorithm reducing the computational complexity using EM algorithm, and evaluate this algorithm through some simulations.

    CiNii J-GLOBAL

  • On the Condition of ε-Achievable Overflow Thresholds for the Parametric Compound Source

    NOMURA Ryo, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report   107 ( 42 ) 37 - 41  2007.05

    　View Summary

    In the previous result, we generalized the achievability of variable-length coding from two viewpoints. One is the definition of an overflow probability, and the other is the definition of an achievability. We defined the overflow probability as the probability of codeword length, not per symbol, is larger than η_n and we introduce the ε-achievability of variable-length codes that implies an existence of a code for the source under the condition that the overflow probability is smaller than or equal to ε. Then, we showed the condition of ε-achievability for some restricted sources given ε. In this paper, at first we define the ε-achievability for the parametric compound source. Then we show the sufficient condition for the ε-achievability.

    CiNii

  • A Study on Relation between Orthogonal Design and Dual Codes

    浮田善文, 松嶋敏泰

    電子情報通信学会技術研究報告   IT2006-107 ( 597(ISEC2006 140-174) ) 131 - 136  2007.03

    J-GLOBAL

  • A Note on Nonstationary Poisson Model with the Consideration of Change Factors

    SUZUKI KOICHI, HORII SHUNSUKE, MATSUSHIMA TOSHIYASU

    IEICE technical report   106 ( 524 ) 83 - 88  2007.01

    　View Summary

    As a model for arrival request, a nonstationary poisson model which uses the Fourier series development for intensity function had been proposed. The model has a weakness that when some large deviations exist, the degree of the model tends to large. Meanwhile, when the system has a start and a closure, the arrival requenst tends to increase just after the start or just before the closure. In this research, we propose nonstationary poisson models with the consideration of change factors.

    CiNii J-GLOBAL

  • 画像に対する状態表現を用いたモデル化と無歪み符号化

    西村信哉, 堀井俊佑, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   30th  2007

    J-GLOBAL

  • スペルミスを伴う形態素解析に関する一考察

    前田康成, 吉田秀樹, 藤原祥隆, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集(CD-ROM)   30th  2007

    J-GLOBAL

  • 盗聴・改ざんに対して耐性を持つネットワーク符号化について

    堀井俊佑, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   30th  2007

    J-GLOBAL

  • Viterbiアルゴリズムにおける尤度比検定を用いたリスト復号が保持すべきサバイバの本数について

    新家稔央, 桑子雅史, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   30th  2007

    J-GLOBAL

  • Gilbert-Elliott通信路に対するLDPC符号のロバスト性に関する密度発展法による解析

    小林学, 松嶋敏泰, 平澤茂一

    情報理論とその応用シンポジウム予稿集(CD-ROM)   30th  2007

    J-GLOBAL

  • A performance of the LZ78 code for Non-prefix-free Word-valued source

    ISHIDA Takashi, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report   106 ( 516 ) 13 - 18  2007

    　View Summary

    A word-valued source (WVS) is a new class of information source models. It is defined as a source which has a probability distribution over a word set. When the word set is prefix-free, it has been shown that there exists entropy rate of the source with simple expression and the AEP holds. Furthermore, there are theoretical arguments about universal code for the source. However, when the word set is not prefix-free, it has been shown only the upper bound and lower bound on the entropy rate of the source. In this paper, we investigate the property of the non-prefix-free WVS comparing the redundancy of the LZ78 code for various sources by numerical experiments.

    CiNii J-GLOBAL

  • Shortened and Concatenated Collusion-secure Codes for Digital Fingerprinting

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Technical Report, vol. 107,no.42, IT2007-6, pp.31-36, May 2007.    2007

  • An Adaptive Decoding Algorithm of LDPC Codes over the Binary Erasure Channel

    Gou Hosoya, Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proc. 2007 Hawaii and SITA Joint Conference on Information Theory, Hawaii, U.S.A., May 2007.    2007

  • Shortening Methods of Collusion-Secure Codes for Digital Fingerprinting

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proc. 2007 Hawaii and SITA Joint Conference on Information Theory, Hawaii, U.S.A., May 2007.    2007

  • A Generalization of the Parallel Error Correcting Codes by Allowing Some Random Errors.

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   90-A ( 9 ) 1745 - 1753  2007

    DOI

  • A Note on the overflow probability of lossless codes

    NOMURA Ryo, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      29 ( 2 ) 799 - 802  2006.11

    CiNii

  • A Note on Transmission Schemes with Unequal Error Protection Codes and a Feedback Channel

    KOBAYASHI Naoto, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      29 ( 2 ) 815 - 818  2006.11

    CiNii

  • A Note on a Construction of Error-Correcting Codes for Channels with Memory

    MASUI Yoichi, KOBAYASHI Naoto, MATSUSHIMA Toshiyasu

      29 ( 1 ) 1 - 4  2006.11

    CiNii

  • A study of interactive source coding of correlated sources

    YOSHIDA Takahiro, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      29 ( 1 ) 355 - 358  2006.11

    CiNii J-GLOBAL

  • A note on estimation of states in HMM with unknown parameters

    MAEDA Yasunari, YOSHIDA Hideki, FUJIWARA Yoshitaka, MATSUSHIMA Toshiyasu

      29 ( 2 ) 609 - 612  2006.11

    CiNii J-GLOBAL

  • Multiuser Detection Algorithms for CDMA based on the Massage Passing Algorithms (HISC2006)

    Horii Shunsuke, Suko Tota, Matsushima Toshiyasu

    IEICE technical report   106 ( 60 ) 17 - 22  2006.05

    　View Summary

    Optimal multiuser detection for the direct sequence code division multiple access (DS-CDMA) channel is known to be NP-hard, i.e., its computational complexity increase exponentially with the number of users. If regarding the detection problem as the probabilistic inference problem, one of the principled approaches to derive the algorithm for the detection problem is to apply the message passing algorithm such as the belief propagation (BP) algorithm and the concave convex procedure (CCCP) on a graph after obtaining the graphical representation of the problem. But it has been reported that the computational complexity of the resulting algorithms are exponentially increasing as the number of users increases since the graphical representation of the detection problem become a complete bipartite graph. Consequently it has been proposed that to reduce the computational complexity through approximating the algorithms with the central limit theorem. In this paper, we suggest that we can reduce the computational complexity of the message passing algorithms for the detection problem by converting the graph structure, and as a result, the message passing algorithms can be applied in the same way of the definition without approximation.

    CiNii

  • A Note on Multi-topic Document Classification Method Based upon Statistical Decision Theory

    MAEDA Yasunari, YOSHIDA Hideki, FUJIWARA Yoshitaka, MATSUSHIMA Toshiyasu

    IEICE technical report   105 ( 665 ) 147 - 152  2006.03

    　View Summary

    In this paper we treat multi-topic document classification problem. In previous researches some theoretical optimality is guaranteed when the number of data for learning is infinite. We propose new multi-topic document classification methods that minimize error rate with reference to the Bayes criterion when the number of data for learning is finite. And we also propose approximate algorithms in order to reduce computational complexity.

    CiNii J-GLOBAL

  • An Algorithm for Computing the Hiding Capacity of Information Hiding

    YASUI Kensuke, SUKO Tota, MATSUSHIMA Toshiyasu

    IEICE technical report   105 ( 665 ) 177 - 182  2006.03

    　View Summary

    There are digital watermarking and fingerprinting (generically calling information hiding) as technique to protect illegal copy or redistribution of digital contents such as images, audio, and video. These are techniques which hide information related to author (user) under contents on the condition that it is imperceptible. Information hiding requires the property that hidden information isn't erased after suffering transformation (data compression, signal processing, etc). The supremum of information rates which can be decoded from contents without error after transformation calls hiding capacity. Moulin et al. formalized information hiding by information theoretic analysis and obtained hiding capacity, but they didn't compute it. In this paper, we propose an algorithm to compute hiding capacity by applying Arimoto-Blahut algorithm.

    CiNii J-GLOBAL

  • 秘密情報を持つBroadcast ChannelのSecrecy Capacity計算アルゴリズム

    安井謙介, 須子統太, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集   29th ( Vol.1 )  2006

    J-GLOBAL

  • A Modification Method for Constructing Low-Density Parity-Check Codes for Burst Erasures

    Gou Hosoya, Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Technical Report   IT2005-121   153 - 158  2006

  • On Factorial Effects Corresponding to Orthogonal Arrays with Unequal Strength

    SAITO Tomohiko, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report   vol.106 ( no.60 ) 53 - 58  2006

    　View Summary

    Orthogonal Arrays (OAs) have been playing important roles in the field of experimental design. It is well known that OAs are closely related to error-correcting codes, and many good OAs are constructed from error-correcting codes. And factorial effects that can be estimated with OAs corresponding to error-correcting codes are clarified. On the other hand, in our past researches, we focused on the relation between OAs and unequal error protection codes (UEP codes). OAs corresponding to UEP codes are called OAs with unequal strength (UOAs), where OAs corresponding to error-correcting codes are called OAs with equal strength. We showed that UOAs are more practical than OAs with equal strength, and proposed some construction methods of UOAs from UEP codes. But, in the researches, we only showed some examples of factorial effects that can be estimated with UOAs, so we had never clarified these factorial effects as well as OAs with equal strength. In this paper, we clarify factorial effects that can be estimated with UOAs.

    CiNii

  • A New Class of Traceability Codes for Digital Fingerprinting

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Technical Report   vol.106 ( no.60 ) 13 - 18  2006

  • New traceability codes against a generalized collusion attack for digital fingerprinting

    YAGI H.

    Proc. 2006 Int. Workshop on Information Security Applications (WISA2006), Jeju Island, Korea, Aug.     569 - 584  2006

    DOI CiNii

  • Fast Algorithm for Generating Candidate Codewords in Reliability-Based Maximum Likelihood Decoding.

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences   E89-A ( 10 ) 2676 - 2683  2006

    DOI

  • A Modification Method for Constructing Low-Density Parity-Check Codes for Burst Erasures

    HOSOYA Gou, YAGI Hideki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE Trans. Fundamentals, A   E89-A ( 10 ) 2501 - 2509  2006

    　View Summary

    We study a modification method for constructing low-density parity-check (LDPC) codes for solid burst erasures. Our proposed modification method is based on a column permutation technique for a parity-check matrix of the original LDPC codes. It can change the burst erasure correction capabilities without degradation in the performance over random erasure channels. We show by simulation results that the performance of codes permuted by our method are better than that of the original codes, especially with two or more solid burst erasures.

    DOI CiNii

  • Performance of Low-Density Parity-Check Codes for Burst Erasure Channels

    Gou Hosoya, Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proc. of 2006 International Symposium on Information Theory and its Applications (ISTIA2006), Seoul, Korea, Oct. 2006.    2006

  • A generalization of the parallel error correcting codes

    YAGI H.

    Proc. 2006 IEEE Inf. Theory Workshop, Chengdu, China, Oct.     229 - 233  2006

    CiNii

  • On Correctable Burst-Erasure Lengths for LDPC Codes with Column Permuted Parity-Check Matrices

    Gou Hosoya, Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proc. 29th Symposium on Information Theory and its Applications (STIA2006), pp.645-648, Hakodate, Nov. 2006.    2006

  • Decoding Performance of Linear Parallel Error Correcting Codes

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Proc. 29th Symposium on Information Theory and its Applications (STIA2006), pp.189-192, Hakodate, Nov. 2006.    2006

  • HMM通信路に対するEM復号の復号誤り確率の評価法

    小林 学, 八木 秀樹, 松嶋 敏泰, 平澤 茂一

    第29回情報理論とその応用シンポジウム予稿集, 函館，2006年11月.   29th ( Vol.1 )  2006

    J-GLOBAL

  • A Note on the Construction of Orthogonal Designs Using Error Correcting Codes

    SAITO Tomohiko, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      27 ( 2 ) 463 - 466  2005.12

    CiNii J-GLOBAL

  • Redundancy of Bayes Codes for Nonstationary Sources with Piecewise Constant Parameters

    SUKO Tota, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      27 ( 2 ) 523 - 526  2005.12

    CiNii J-GLOBAL

  • A Note on the Asymptotics of Bayes Prediction for Hierarchical Models

    TAKUMI Takeo, SUKO Tota, MATSUSHIMA Toshiyasu

      27 ( 2 ) 639 - 642  2005.12

    CiNii J-GLOBAL

  • A Heuristic Search Algorithm with the Reduced List of Test Error Patterns for Maximum Likelihood Decoding

    YAGI Hideki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      27 ( 2 ) 571 - 574  2005.12

    CiNii

  • A Note on Universal Coding Algorithm with the BWT

    SUKO Tota, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      28 ( 1 ) 315 - 318  2005.11

    CiNii J-GLOBAL

  • Bayes Optimal Multi User Detection for DS/CDMA Systems with Time-Varying Group of Active Users

    HORII Shunsuke, SUKO Tota, MATSUSHIMA Toshiyasu

      28 ( 2 ) 781 - 784  2005.11

    CiNii J-GLOBAL

  • A Selective-Repeat ARQ Scheme with Finite Receiver Buffer Based on Statistical Decision Theory

    AMEMIYA Koji, KOBAYASHI Naoto, MATSUSHIMA Toshiyasu

      28 ( 2 ) 757 - 760  2005.11

    CiNii J-GLOBAL

  • A Decoding Algorithm of Low-Density Parity-Check Codes Using Decisions of Erasure Correcting

    HOSOYA Gou, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      28 ( 1 ) 5 - 8  2005.11

    CiNii

  • A Note on an Error-Correcting System with a Feedback Channel

    KOBAYASHI Naoto, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      28 ( 1 ) 343 - 346  2005.11

    CiNii J-GLOBAL

  • A Study of Calculating Information Hiding Capacity of Digital Watermarking

    YASUI Kensuke, SUKO Tota, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   105 ( 191 ) 29 - 34  2005.07

    　View Summary

    Digital watermarking is one of the techniques to protect copyright ownership of digital contents such as images, audio, and video. Watermarking protects copyright ownership by hiding information related to author (watermark) within contents on the condition that it is imperceptible. One of the problems of watermarking is how we increase reliable information of watermark after suffering data compression, signal processing, etc. (information hiding capacity). Moulin formalized watermarking by information theoretic analysis and obtained information hiding capacity. But he didn't calculate it numerically. In this paper, we propose an algorithm to calculate a lower bound of information hiding capacity by changing attacker's assumption in Moulin's model of watermarking.

    CiNii J-GLOBAL

  • An Algorithm of Bayes Coding for FSMX Sources to Reduce Required Memory Size

    NAKANO Akira, KOBAYASHI Naoto, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   105 ( 191 ) 47 - 52  2005.07

    　View Summary

    Bayes code is one of universal source codings, such that a class of the probabilistic model of source is known but the parameters of the probabilistic model are not known. Bayes code provides Bayes optimality in term of redundancy. Matsushima proposed Bayes coding algorithm for FSMX sources. In his algorithm, coding probability is calculated using a context tree. The algorithm, however, needs enormous memory if it encodes some sequences, because upper bound of required memory size is not less or equal to O(n) for sequence size n. In this paper, we propose Bayes coding algorithm for FSMX sources to reduce required memory size, and we investigate its performance. In addition, if we encode sequence x^n in our algorithm, required memory size is O(n). Time complexity of our algorithm is equivalent to Matsushima's algorithm.

    CiNii J-GLOBAL

  • Fast Algorithm for Generating Candidate Codewords in Reliability-based Maximum Likelihood Decoding

    YAGI Hideki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   105 ( 84 ) 1 - 6  2005.05

    　View Summary

    The reliability-based heuristic search methods for maximum likelihood decoding (MLD) generate test error patterns (or, equivalently, candidate codewords) according to their heuristic values. Test error patterns are stored in lists and this makes the space complexity crucially large for MLD of long block codes. Then some studies have proposed methods for reducing the list size of test error patterns in these MLD algorithms including the well-known A^* decoding algorithm proposed by Han et al. In this paper, we propose a new method for reducing the time complexity of generating candidate codewords by storing some already generated candidate codewords. Simulation results show that the increase of memory size is almost negligible.

    CiNii

  • A Note on the Construction of Nonlinear Unequal Orthogonal Arrays from Error-Correcting Codes

    SAITO Tomohiko, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE Technical Report   105 ( 84 ) 13 - 18  2005.05

    　View Summary

    Orthogonal arrays have been used in the field of experimental design. Hedayat and Sloane showed the relation between orthogonal arrays and error-correcting codes[1]. And they proposed some construction methods of both linear and nonlinear orthogonal arrays from error-correcting codes. On the other hand, the paper[5] defined unequal orthogonal arrays as new class. It showed that unequal orthogonal arrays are more applicable to experimental design. Furthermore, it showed the relation between unequal orthogonal arrays and unequal error-correcting codes[3], and proposed the construction method of unequal orthogonal arrays from unequal error-correcting codes. But orthogonal arrays from this construction method are all linear. In this paper, we clarify the relation between nonlinear unequal orthogonal arrays and codes. And we propose one of construction methods of nonlinear unequal orthogonal arrays from error-correcting codes.

    CiNii

  • インターネットを用いた研究支援環境～電子会議システム～

    野村亮, 石田崇, 中澤真, 鴻巣敏之, 松嶋敏泰, 平澤茂一

    経営情報学会 2005年度春季全国研究発表大会予稿集   2005   254 - 257  2005

    J-GLOBAL

  • インターネットトラヒックのポアソン分布の密度パラメータが時間変動する時系列モデルを用いた解析に関する一考察

    小泉大城, 松嶋敏泰, 平澤茂一

    2005年FIT（情報科学技術フォーラム）論文集   L-016 ( 4 ) 35 - 38  2005

    CiNii J-GLOBAL

  • A Relation between Erasure Correcting and Error Correcting of Low-Density Parity-Check Codes

    細谷剛, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   vol.105 ( no.311 ) 13 - 17  2005

    J-GLOBAL

  • アプリオリアルゴリズムを用いた指定精度を保証するマトリックスクラスタリング手法

    小林 学, 松嶋 敏泰, 平澤 茂一

    経営情報学会春季全国大会予稿集   vol.1   50 - 53  2005

  • 有限幾何に基づくFingerprintingのための結託耐性符号,

    八木秀樹, 松嶋敏泰, 平澤茂一

    第28回情報理論とその応用シンポジウム予稿集   28th ( Vol.2 ) 701 - 704  2005

    J-GLOBAL

  • A Note on Improvement of a Fast Correlation Attack

    HOSOBUCHI Satoshi, SAITO Tomohiko, MATSUSHIMA Toshiyasu

      27 ( 1 ) 37 - 40  2004.12

    CiNii J-GLOBAL

  • Non-perfectly secure identity based decentralized key distribution system

    YOSHIDA Takahiro, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      27 ( 1 ) 327 - 330  2004.12

    CiNii J-GLOBAL

  • A Note on Decoding of Low Density Parity Check Codes with Small-Loop

    KOBAYASHI Naoto, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      27 ( 1 ) 267 - 270  2004.12

    CiNii J-GLOBAL

  • Redundancy of Bayes Coding for Nonstationary Sources with Piecewise Constant Parameters

    SUKO Tota, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   104 ( 229 ) 23 - 28  2004.07

    　View Summary

    In this paper we treat universal source coding when the parameters of the probabilistic model of source are known. Bayes code is one of the wellknowm universal codes. Bayes code has Bayes optimality in point of minimization of redundancy. Recently, many researches of Bayes code for nohstationary sources are done. Researches for sources with piecewise constant parameters are one of them. Each sections are visible to stationary sources. But these sources have abruptly changing parameters. And they are treated as nonstationary sources. But the Asymptotic character of mean redundancy for this source is not known. In this paper, we evaluate asymptotic mean redundancy of this source with the conditions of change number is not kown. And we show that Bayes code has universality with some condtions.

    CiNii J-GLOBAL

  • A ramp model for key distribution schemes

    YOSHIDA Takahiro, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    Technical report of IEICE. ISEC   104 ( 53 ) 69 - 74  2004.05

    　View Summary

    A key distribution scheme is a method to distribute off-line initial private pieces of information among a set of users, such that each group of a given size can compute a common key for secure conference. In this paper, we consider a ramp model for key distribution scheme. In the ramp model, the required resources can be reduced at the cost of a secerity degradation which depends on the size of users. We define a ramp model for key distribution scheme, show lower bounds on the size of the piece of a user's information and design a ramp model for key distribution scheme.

    CiNii J-GLOBAL

  • On the Channel Capacity of Universal Channel Coding

    NOMURA Ryo, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    Technical report of IEICE. ISEC   103 ( 713 ) 7 - 11  2004.03

    　View Summary

    In this paper, we investigate the channel capacity in the case that we do not know the probabilistic model of the channel. First we show the channel capcity in the universal case. To show our main theorem we introduce the decoding scheme that minimizes the probability of error with respect to Bayes criteria.

    CiNii

  • Viterbiアルゴリズムを用いた可変サイズのリスト復号における誤り指数

    新家稔央, 松嶋敏泰, 平沢茂一

    情報理論とその応用シンポジウム予稿集   27th ( Vol.2 )  2004

    J-GLOBAL

  • A Note on Relations between Learning from Queries and Sequential Experimental Design

    浮田善文, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   AI2003-63 ( 623(AI2003 63-75) ) 1 - 6  2004.01

    J-GLOBAL

  • Word-valued sourceから出現する系列の単語分割について

    石田崇, 松嶋敏泰, 平澤茂一

    第27回情報理論とその応用シンポジウム予稿集，岐阜   27th ( Vol.1 ) 135 - 138  2004

    J-GLOBAL

  • A decoding method of low-dencity parity-check codes over binary symmetric channel

    Gou Hosoya, Toshiyasu Matsushima, Shigeichi Hirasawa

    第27回情報理論とその応用シンポジウム予稿集，岐阜    2004

  • Parallel Propagation Algorithms for Tailbiting Convolutional Codes

    MATSUSHIMA Toshiyasu, MATSUSHIMA Tomoko K., HIRASAWA Shigeichi

      26 ( 2 ) 445 - 448  2003.12

    CiNii

  • A note on one of the approximation methods of the prediction based on Bayes decission theory

    EGUCHI Kimimori, SUKO Tota, MATSUSHIMA Toshiyasu

      26 ( 2 ) 703 - 706  2003.12

    CiNii J-GLOBAL

  • On the Security of Collision Free Hash Function Family

    SHIBUYA Tomonari, SAITO Tomohiko, MATSUSHIMA Toshiyasu

      26 ( 2 ) 609 - 612  2003.12

    CiNii J-GLOBAL

  • Bayes Coding for Sources with Piecewise Constant Parameters

    SUKO Tota, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      26 ( 1 ) 165 - 168  2003.12

    CiNii J-GLOBAL

  • Prediction Algorithm for Decision Tree Model

    SUKO Tota, NOMURA Ryo, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Theoretical foundations of Computing   103 ( 246 ) 93 - 98  2003.07

    　View Summary

    Conventionally, decision tree generation algorithm has been used when performing prediction using the decision tree model. It can be considered that these are the model selection algorithm in the basis to which data was given. And, It predicts using the model chosen by the basis to which data was given. Therefore, it was very difficult to perform theoretical evaluation to the rate of a prediction error. In this work, we shows the prediction algorithm which makes the rate of an average prediction error the minimum. First, we re-formulize a decision tree model as a parametric stochastic model. The optimal prediction algorithm based on Bayes decision theory is shown using the model. Furthermore, the algorithm which calculates a prediction distribution efficiently by restraining a model class is described.

    CiNii J-GLOBAL

  • Modeling and Forecasting of Correlated Time Series State Space Models

    鈴木悠哉, 須子統太, 松嶋敏泰

    電子情報通信学会技術研究報告   103 ( 215 ) 87 - 92  2003.07

    CiNii J-GLOBAL

  • A Study of Modeling of Nonstationary Time Series based on Poisson Distribution

    IWATA Kinya, YOSHIDA Takahiro, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   103 ( 215 ) 93 - 98  2003.07

    　View Summary

    Gaussian and linear state space model is a model for nonstationary time series. When we deal with non-Gaussian data based on the poisson distribution, however, this model is not adequate for the analysis. So some approaches to extend Gaussian and linear state space model have been proposed. For example, West et al proposed the Dynamic Generalized Linear Model. One of problems on his model is that exact posterior distribution of the parameter can not be obtained. In this paper, we propose model that enable us to calculate exact posterior distribution of the parameter analytically. Additionally, we show some simulataion results to make sure properties of this model.

    CiNii J-GLOBAL

  • A Study of Analysis of Alternate Decoding Algorithm of Convolutional Codes

    OSAWA Masayuki, NOMURA Ryo, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   103 ( 215 ) 57 - 62  2003.07

    　View Summary

    The maximum a posterior probability decoding of Low Density Parity Check (LDPC) Codes and Turbo Codes is one of the most active subjects in research of error correcting codes. Recently, various methods of analyzing decoding algorithm of these codes using Monte Carlo method partially, not entirely, are proposed. The representative methods of this type are EXIT-CHART for BCJR algorithm on Turbo Codes and for sum product algorithm on LDPC Codes and Gaussian Approximation for BCJR algorithm on Turbo Codes. On the other hand, alternate algorithm for generalized posterior probability on LDPC Codes, Convolutional Codes and Turbo Codes turned out to be superior to sum product algorithm or BCJR algorithm on those codes in many points by simulations. In this paper we consider a method of analyzing alternate algorithm for generalized posterior probability on Convolutional Codes using Monte Carlo Filter method partially.

    CiNii J-GLOBAL

  • A Note on Learning Boolean Functions by Using Orthogonal Design

    UKITA Yoshifumi, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE transactions on fundamentals of electronics, communications and computer sciences   86 ( 4 ) 975 - 975  2003.04

    CiNii

  • "A Method for Reducing Space Complexity of Reliability based Heuristic Search Maximum Likelihood Decoding Algorithms" The 26th Symposium on Information Theory and Its Applications (SITA2003),

    Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa

    第26回情報理論とその応用シンポジウム予稿集   pp.185-188  2003

  • "語頭条件を満たさないWord-Valued Sourceモデルに関する一考察"

    石田崇, 松嶋敏泰, 平澤茂一

    第26回情報理論とその応用シンポジウム予稿集   pp.77-80 ( Vol.1 )  2003

    J-GLOBAL

  • Properties of a Word-valued Source with a Non-prefix-free Word Set

    ISHIDA Takashi, GOTO Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   IT2003-5, pp23-28 ( 99 ) 23 - 28  2003

    　View Summary

    Recently, word-valued source is proposed as a new class of source models. A word-valued source is defined as a source which has a probability distribution over word set. When the word set is prefix-free, it has been shown that there exists entropy rate of the source with simple expression and the AEP holds. However, when the word set is not prefix-free, it has been shown only the upper bound and lower bound on the entropy rate of the source. In this paper, we verify the entropy rate of the source by numerical computations for some source models in order to clarify the properties of the word-valued source.

    CiNii J-GLOBAL

  • "インターネットを用いた研究支援システム"

    中澤真, 野村亮, 鴻巣敏之, 松嶋敏泰

    私立大学情報教育協会平成15年度大学情報化全国大会予稿集，東京   pp.72-73  2003

  • A Generalized Posterior Probability and Its Calculation Procedures

    MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   102 ( 494 ) 1 - 8  2002.12

    　View Summary

    The posterior probability P(Y|X = x) given the evidence X = x is calculated by the ordinary probabilistic reasoning. In the case that an evidence is given by the distribution of random variables such as P(X = x) =p_x this type of evidence is called distribution-evidence in the previous research. The probabilistic reasoning given distribution-evidence has been formalized as generalized probabilistic reasoning. We show that the posterior distribution calculated by the generalized probabilistic reasoning is the distribution that is closest to the prior distribution with Kullback-Leibler information under the restriction of marginal distributions. Iterative Proportional Fitting Procedure (IPFP) can be applied to the procedure of the generalized probabilistic reasoning. We explain efficient propagation algorithms based on IPFP for calculating marginal generalized posterior distributions on extended junction graphs (EJG). The propagation algorithms are regarded as a generalization of HUGIN and the sum-product algorithm. The propagation algorithms can be applied to not only generalized probabilistic reasoning but also many research fields such as decoding problem.

    CiNii J-GLOBAL

  • A Note on Learning Boolean Functions from Queries Composed by Sequential Experimental Design

    UKITA Yoshifumi, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report   COMP2002-52 ( 490 ) 47 - 53  2002.11

    　View Summary

    In this paper, we propose the algorithm to output the boolean function which does not contradict in the result of the queries by using sequential experimental design. Furthermore, we show posterior probability of the outputted function is the biggest when a certain assumption can be done.

    CiNii J-GLOBAL

  • A study of calculating channel capacity for (2,2;2)-Multiple Access Channel

    EGUCHI Kimimori, NOMURA Ryo, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   102 ( 198 ) 25 - 30  2002.07

    　View Summary

    Shannon defined the channel capacity which can send the maximum information without faults. Channel capacity has been studied by Arimoto, Blahut R.E.and so on as the problem of calculating the maximum mutual information. Ahlswede defined the channel capacity for the multiple channel. Recently Watanabe proposed the algorithm of calculating the total capacity of (2,2;2)-MAC by Newton method. MAC stands for Multiple Access Channel. (2,2;2) means that 2 user send message to 1 receiver with 2 alphabets. In this paper we consider the total capacity of (2,2;2)-MAC. This total capacity is also the maximum mutual information. We propose the method without iterative calculating.

    CiNii J-GLOBAL

  • A Study of Decoding Algorithm of Low Density Parity Check Code

    KOBAYASHI Naoto, NOMURA Ryo, MATSUSHIMA Toshiyasu

    Technical report of IEICE. SST   101 ( 730 ) 39 - 44  2002.03

    　View Summary

    The maximum a posteriori probability decoding of Turbo code and Low Density Parity check code is one of the most active subjects in research of error correcting code. Sum-Product(SP) algorithm is used for those, but the performance of SP becomes bad when a small loop of length 4 is in the Bayesian Network .An algorithm proposed by Matsushima on the probabilistic model equal to Junction Graph does not have such a fault. In this paper we propose a method of construction of (Normalized) Junction Graph using the algorithm for decoding of LDPC code, and compare the performance of it and SP.

    CiNii J-GLOBAL

  • ベイズ決定理論に基づくロバストなパターン認識手法に関する一考察

    桑田修平, 吉田隆弘, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集   25th ( Vol.1 )  2002

    J-GLOBAL

  • 誤り訂正符号構成法を利用した直交計画の構成法に関する一考察

    斉藤友彦, 吉田隆弘, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集   25th ( Vol.2 )  2002

    J-GLOBAL

  • 拡張された階層モデルにおける予測アルゴリズムについて

    須子統太, 野村亮, 松嶋敏泰

    情報理論とその応用シンポジウム予稿集   25th ( Vol.2 )  2002

    J-GLOBAL

  • 多端子情報源符号化に基づいた分散協調問題の定式化

    吉田隆弘, 松嶋敏泰, 平沢茂一

    情報理論とその応用シンポジウム予稿集   25th ( Vol.1 )  2002

    J-GLOBAL

  • リスト復号に対する判定帰還方式LR+THの誤り指数について

    新家稔央, 松嶋敏泰, 平沢茂一

    情報理論とその応用シンポジウム予稿集   25th ( Vol.2 )  2002

    J-GLOBAL

  • 単語単位で系列を出力する情報源の性質について

    石田崇, 後藤正幸, 松嶋敏泰, 平澤茂一

    第25回情報理論とその応用シンポジウム予稿集   pp.695-698 ( Vol.2 ) 695 - 698  2002

    CiNii J-GLOBAL

  • Computational Source Information Model and its Algorithm

    NAKAZAWA Makoto, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   pp.19-24 ( 331 ) 19 - 24  2002

    　View Summary

    Recently, grammar based codes are researched in the area of lossless source coding. However, it is not clear which formal grammar is appropriate in Chomsky hierarchy for information compression. In order to clarify this, we propose a computational information source model. Computational information source models generate messages in terms of their probabilistic formal grammars. We present each characterization for probabilistic regular grammar based information source and probabilistic context-free grammar based information source. In the case when the parameters of these information sources are known, the lossless compression algorithms and their time complexity are shown. At the last, it is shown that a grammar based code is a universal code with respect to the family of probabilistic context-free grammars information sources.

    CiNii J-GLOBAL

  • 「インターネットを用いたゼミと研究指導」実用化報告

    野村亮, 中澤真, 松嶋敏泰, 平澤茂一

    2002PCカンファレンス    2002

  • A Note on Computational Learning and Information Compression.

    中沢真, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   pp.37-42 ( 66(IT2002 1-10) )  2002

    J-GLOBAL

  • Distributed Cooperative Problem based on Multi-Terminal Systems

    YOSHIDA Takahiro, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

      24 ( 1 ) 367 - 370  2001.12

    CiNii

  • A Note on Learning Boolean Functions by using Orthogonal Design under Bayesian Decision Theoretic Formulation

    UKITA Yoshifumi, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Theoretical foundations of Computing   COMP2001-59 ( 431 ) 51 - 58  2001.11

    　View Summary

    In this paper, we consider boolean functions learning from the position which is different from the position of the computational learning theory. We propose the algorithm that input sets to query is orthogonal design of experimental design, and evaluate the algorithm

    CiNii J-GLOBAL

  • A study of coding for sources with nonstationary parameter

    YASUDA Gouki, NOMURA Ryo, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   101 ( 177 ) 25 - 30  2001.07

    　View Summary

    Bayes code is one of the welknown universal codes. Bayes code has asymptotic optimality and Bayes optimality in point of minimization of mean redundancy. Bayes coding algorithms for stationary sources are proposed by Willems et al., Matsushima et al. Recently, Bayes code for nonstationary sources has been studied. However, any studies have problems in point of the nonstationary settings. In this paper, we propose a nonstationary source model and Bayes coding algorithm for the source. Moreover we consider properties of the proposed code from some simulations.

    CiNii J-GLOBAL

  • A Formulation of Distributed Cooperative Problem based on Multi-Terminal Systems

    YOSHIDA Takahiro, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   101 ( 177 ) 37 - 42  2001.07

    　View Summary

    We consider the kind of distributed cooperative systems defined as follows. First, a number of agents make observations of an information of correlative states. Second, the agent receives the partial information from other agent and sends the part of observed information to other agent. Finally, the agent utilizes observed information to the full for group decision. In this paper, we apply a multi-terminal systems to a distributed cooperative system and formulate a distributed cooperative problem based on Bayes decision theory. In tha case that loss function is the logarithmic loss function, we shall derive the Bayes rule that minimizes Bayes risk, and show that Bayes risk of the Bayes rule is represented as two types of the mutual information.

    CiNii J-GLOBAL

  • 状態空間モデルを用いた時系列解析に関する一考察 モンテカルロフィルタにおけるリサンプリング方法について

    桑田修平, 吉田隆弘, 松嶋敏泰

    日本経営工学会秋季研究大会予稿集   2001  2001

    J-GLOBAL

  • ブロックターボ符号に対するインタリーバの構成法と最小距離

    小林学, 松嶋敏泰, 平澤茂一

    第24回情報理論とその応用シンポジウム   P.95～P.98  2001

  • 「インターネットを用いた研究活動支援システム」システム構成と評価

    野村亮, 中澤真, 鴻巣敏之, 松嶋敏泰, 平澤茂一

    2001年日本経営学会秋季研究発表大会   2001  2001

    J-GLOBAL

  • A Note on Formal Languages and Data Compression.

    中沢真, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   P.19～P.24 ( 407(IT2001 43-48) )  2001

    J-GLOBAL

  • 「インターネットを用いた研究活動支援システム」システム構成

    平澤茂一, 松嶋敏泰, 鴻巣敏之, 酒井哲也, 中澤真, 李相協, 野村亮

    2001PCカンファレンス    2001

  • Generator Matrices of Block Turbo Codes and Their Performance Analysis

    KOBAYASHI Manabu, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   P.1～P.6 ( 177 ) 1 - 6  2001

    　View Summary

    In 1993 C.Berrou et.al. have proposed turbo codes which achieved low BER with a SNR per information bit close to Shannon's theoretical limit on AWGN channel. H.Hagenauer et.al. also have proposed block turbo codes which consist of two systematic block codes concatenated in parallel. In this paper we analyze the performance of the block turbo codes by considering them as one-dimensional codes. At first we find generator matrices of block turbo codes. We show that it is possible to increase the lower bound of minimum distance by restricting permutation matrices. Furthermore we propose a method to calculate low weight distribution with low complexity. Simulation results show that block turbo doces achieve low BER by restricting permutation matrices.

    CiNii J-GLOBAL

  • A Note on Wavelet Packet Noise Reduction Using Bayes Theory

    KITAHARA Masaki, NOMURA Ryo, MATSUSHIMA Toshiyasu

    Technical report of IEICE. DSP   100 ( 515 ) 9 - 16  2000.12

    　View Summary

    A method that applies Bayes theory on using wavelet packets to the problem of estimating an unknown signal currupted by noise has been proposed in the previous research. Despite its Bayesian aproach, it is not completely Bayes optimal when the loss fuction is something useful in estimating the signal like the wquared error loss. In this paper, we deal with the Bayesian optimized estimator of the squared error loss. When applying Bayesian optimization, it involves wavelet packet basis weighting which requires high computational complexity. We propose an algorithm with takes account the binary tree structure of the wavelet packet bases which computes the Bayes optimal estimator in O(N log N). We will comfirm the Bayesian optimality through some expiriments.

    CiNii J-GLOBAL

  • A Note on Learning Boolean functions from queries by Using Fourier Transform.

    浮田善文, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   COMP2000-56 ( 449(COMP2000 50-56) ) 49 - 55  2000.11

    J-GLOBAL

  • An Algorithm of Arithmetic Code Considering the Error on the Estimation of Probability

    HIRAI Masato, NOMURA Ryo, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   100 ( 174 ) 25 - 30  2000.07

    　View Summary

    In loss-less coding, when the probability ditribution of source is given, the lower bound of average codeword length is given by entropy-rate. It's also given by universal coding asymptotically when the probability distribution of source isn't given. In general, universal codings have a function for estimating the probability distribution of source. In the 1-pass universal coding, however, the estimated probability distribution has potential to contain about 1/2log n erorrs for real probability distribution of source which depends on the source length n. In this paper, we propose how to decide the probability to use for encoding in consideration of the error on the estimation of probability in the 1-pass universal coding. Moreover, we give how to decide the number of decimal places in product operation of arithmetic coding. We also analyze the codeword length and compational complexity in using the number of decimal places.

    CiNii J-GLOBAL

  • A study of redundancy of Ziv-Lempel Code

    TODA Yohei, NOMURA Ryo, MATSUSHIMA Toshiyasu

    IEICE technical report. Information theory   100 ( 174 ) 31 - 36  2000.07

    　View Summary

    Recently, Ziv-Lempel code is one of the most active subject in the research of Universal code. Ziv-Lempel code have been proved asymptotically optimal for the stationary source. On the other hand, it is important to see how Ziv-Lempel code perform for the finite source. It is known that Ziv-Lempel code performs not so good especially for the finite Markovian source. For this reason, there are three point of view in the previous research. In this paper, we show the upper bound of the average redundancy of Ziv-Lempel code from a point of view for Markovian source and give some notes from simulation.

    CiNii J-GLOBAL

  • Extension of Reasoning under Uncertainty to Two-array Predicates

    MIZUNO Hiroshi, YOSHIDA Takahiro, MATUSHIMA Toshiyasu

    人工知能学会全国大会論文集   14   291 - 294  2000.07

    CiNii J-GLOBAL

  • Methematical Models in Information-Based Induction Science

    MATSUSHIMA Toshiyasu

      14   36 - 37  2000.07

    CiNii J-GLOBAL

  • 不確実性を含む演繹推論に関する一考察

    鈴木誠, 松嶋敏泰, 平澤茂一

    第23回情報理論とその応用シンポジウム   (427-430)  2000

  • 遺伝的アルゴリズムとk-means法を用いたクラスタリングの効率化

    李相協, 松嶋敏泰, 平澤茂一

    日本経営工学会 春季発表大会   (120-121)  2000

    J-GLOBAL

  • A Study on Difference of Codelengths between Codes based on MDL Principle and Bayes Codes for Given Prior Distributions

    Masayuki Goto, Toshiyasu Matsushima, Shigeichi Hirasawa

    Electronics and Communications in Japan, Part 3   84,4(30-40)  2000

  • 不確実な知識の演繹推論アルゴリズムに関する一考察

    小島 健司, 浮田 善文, 松嶋 敏泰

    第22回情報理論とその応用シンポジウム予稿集     841 - 844  1999.12

    CiNii

  • 質問からのブール関数の学習における学習戦略を求めるアルゴリズム

    浮田 善文, 松嶋 敏泰, 平澤 茂一

    第22回情報理論とその応用シンポジウム予稿集     845 - 848  1999.12

  • Iterative Algorithms for Calculating Probability and Decoding

    MATSUSHIMA Toshiyasu

    Proceedings of the Society Conference of IEICE   1999   251 - 252  1999.08

    CiNii J-GLOBAL

  • Compression and decoding of an inverted file by using syndrome

    FUTAGAMI Tsuneji, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   99 ( 235 ) 55 - 60  1999.07

    　View Summary

    In document retrieval system by keywords, an inverted file is often used. We propose a new method for compressing and decoding it. In the proposed method, it is compressed and decoded at two stages, and syndromes are used in compression. We represent an inverted file by a simple mathematical model and evaluate the system by two quantities. One is size of secondary memory where an inverted file and a decode tree are stored. Another is time complexity for decoding it. The VG bound is used to derive the two quantities. The numerical calculation shows trade-off relation between the two quantities. The time complexity decreases strikingly compared with increase in memory which shows the usefulness of the proposed method.

    CiNii J-GLOBAL

  • A Study Concerned with the Random Excitation of the CELP Speech Coding Algorithm

    KITAHARA Masaki, NOMURA Ryo, MATSUSHIMA Tosiyasu

    IEICE technical report. Information theory   99 ( 187 ) 85 - 90  1999.07

    　View Summary

    The CELP speech coding algorithm is one of the most efficient way of coding speech with low bit rate. The coder and the decoder synthesize speech by filtering a random excitation through a AR filter. There are coders which use sparse excitations which are constructed of only a few pulses. In this paper,we will analize the properties of the sparse excitation in a way to understand the nature of the model. And we will present an example of the way to determine the positions of the pulse which is not the usual procedure of the typical sparse excitation coders.

    CiNii J-GLOBAL

  • Soft-Decision Decoding Methods using Algebraic Decoding Algorithm

    MATSUSHIMA Toshiyasu

    Proceedings of the IEICE General Conference   1999   549 - 550  1999.03

    CiNii J-GLOBAL

  • 音声認識における Hidden Markov Model のパラメータ推定に関する一考察

    高井 望, 浮田 善文, 松嶋 敏泰

    第21回情報理論とその応用シンポジウム予稿集     643 - 646  1998.12

  • 不確実な知識の推論における欠測データの取り扱いに関する一考察

    金澤 裕輔, 浮田 善文, 松嶋 敏泰

    第21回情報理論とその応用シンポジウム予稿集     153 - 156  1998.12

    CiNii

  • 適合フィードバックによる情報検索に関する一考察

    鍛治 美緒, 浮田 善文, 松嶋 敏泰

    第21回情報理論とその応用シンポジウム予稿集     161 - 164  1998.12

  • Reasoning under Uncertainty using Log-Linear Model.

    小島健司, 浮田善文, 松嶋敏泰

    人工知能学会全国大会論文集   12th   308 - 311  1998.06

    J-GLOBAL

  • A Note on Approximate Algorithm on Markov Decision Processes.

    井村真樹, 浮田善文, 松嶋敏泰

    人工知能学会全国大会論文集   12th   56 - 59  1998.06

    J-GLOBAL

  • On performance of prediction using side information

    MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   98 ( 54 ) 7 - 12  1998.05

    　View Summary

    In this paper, prediction using side information is studied. This problem has been investigated as predictive inference in the field of Bayesian theory and as on-line learning in the field of learning theory. The prediction problem under consideration is to predict-log p(y mid x)using given side information x.It is regarded as universal coding given side information. The Bayes risk of the Bayes predictive inference and the maxmini risk correspond to the mutual information of a certain multi-terminal channel and its capacity, respectively. In a certain prediction model, I.e., a multi-terminal channel, the Bayes optimum prediction is derived. Moreover, the asymptotic forms of Bayes risk and maximin risk are shown. This maximin risk is regarded as a difficulty measure of predictive inference and learning.

    CiNii

  • On Error Probability of Model Selection based on Bayes Decision Theory

    GOTOH Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   97 ( 511 ) 43 - 48  1998.01

    　View Summary

    In this paper, we shall discuss on the statistical model selection problems. The purpose of AIC is different from those of BIC and MDL, and AIC has not consistency although BIC and MDL have. Here a question arises. Does AIC have not consistency for the purpose? On the other hand, if we specify the model class, then we can formulate the Bayes optimal model selection for finite samples based on Bayes decision theory. In this paper, we show that model selection based on Bayes decision theory has consistency independent of whether the purpose is prediction of future observation or detection of a true model.

    CiNii J-GLOBAL

  • Asymptotic normality of posterior probability density.

    後藤正幸, 松嶋敏泰, 平沢茂一, 俵信彦

    日本経営工学会春季大会予稿集   1998  1998

    J-GLOBAL

  • Standard of statistic model choice.

    後藤正幸, 松嶋敏泰, 平沢茂一, 俵信彦

    日本経営工学会秋季研究大会予稿集   1998  1998

    J-GLOBAL

  • 帰納 演繹推論と予測-決定理論による学習モデル-

    松嶋敏泰

    第1回 情報論的学習理論ワークショップIBIS'98     1 - 8  1998

    CiNii

  • 決定を考慮したベクトル量子化法の提案

    高井 望, 浮田 善文, 松嶋 敏泰

    第20回情報理論とその応用シンポジウム予稿集     609 - 612  1997.12

  • 直交表現された仮説の学習に関する一考察

    峯松 一彦, 浮田 善文, 松嶋 敏泰

    第20回情報理論とその応用シンポジウム予稿集     701 - 704  1997.12

  • 質問からの学習における予測誤りに関する一考察

    浮田 善文, 松嶋 敏泰

    第20回情報理論とその応用シンポジウム予稿集     697 - 700  1997.12

  • 〔日本品質管理学会〕第55回研究発表会

    松嶋 敏泰

    品質 = Quality : journal of the Japanese Society for Quality Control   27 ( 4 ) 439 - 452  1997.10

    　View Summary

    記事種別: 会議・学会報告・シンポジウム

    CiNii

  • A Note on Trellis Coding for Data Compression

    SUENAGA Takashi, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   97 ( 208 ) 55 - 60  1997.07

    　View Summary

    In trellis coding for data compression, it is difficult to search all codes, and a code is selected by the local search method. In the meantime, the property of the optimal code is shown in Rate-Distortion Theory. In this paper, we propose an algorithm which selects a good code by using the property to avoid selecting a local optimal code as much as possible. To evaluate the algorithm using the property, first we investigate the property of the optimal code for small constraint length by the simulation. Next we compare the result by the algorithm using the property for that by the algorithm not using the property by the simulation.

    CiNii J-GLOBAL

  • A Note on the Decoding Method of Unequal Error Protection Codes

    MIYATA Yoshikuni, KOBAYASHI Manabu, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   97 ( 208 ) 25 - 30  1997.07

    　View Summary

    Unequal error protection (UEP) codes have the differrent error correcting capability for each symbol to be decoded. Among these, UEP codes proposed by W.L.van Gils can use majority logic decoding. This decoding method requires little computational complexity, while its symbol error probability is rather high. In this paper, first, we apply APP decoding to Gils's UEP codes, which is one of the soft decision decoding. And the second, we propose the extended version of APP decoding. This decoder generates the variable size list, which is consist of the candidates of codeword, by monitoring the symbol reliability measure. Then it outputs the symbol to be decoded by the quasi-symbol-posterior probability for the list. We show that this scheme reduces the symbol error probability by adding the small computational efforts.

    CiNii J-GLOBAL

  • A Study on the Algorithm for Learning and Prediction with Context Tree

    SHIMA Yukio, GOTO Masayuki, MATSUSHIMA Tosiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   97 ( 208 ) 73 - 78  1997.07

    　View Summary

    In pattern recognition, the goal is to reduce the decision error probability. The one approach is model selection. Recently the algorithm, which minimizes the error probability, was proposed. This algorithm is based on Bayes decision theory and predicts using mixture of all models in the model class. However, it requires a large amount of the computational complexity. In the paper, we propose an algorithm which approximately outputs Bayes optimal solution by means of the mixture in the subclass. The proposed algorithm adequately reduce the computational complexity.

    CiNii J-GLOBAL

  • On Decoding Method Beyond the BCH Bound

    KOBAYASHI Manabu, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   97 ( 180 ) 31 - 36  1997.07

    　View Summary

    R.E.Blahut has proposed a method for decoding beyond the BCH bound by using the Berlekamp-Massey algorithm. This decoding algorithm is able to correct errors that cannot be obtained by the conventional bounded distance decoding. In this paper we show the complexity of decoding method proposed by Blahut can be reduced by solving equations of unknown discrepancy. Furthermore, we introduce this method to soft-decision decoding using algebraic decoder and show that both the complexity and the probability of decoding error of soft-decision decoding are reduced.

    CiNii J-GLOBAL

  • On Statistical Model Selection based on Bayes Decision Theory

    GOTOH Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   97 ( 180 ) 37 - 42  1997.07

    　View Summary

    In this paper, we analyze the asymptotic properties of the stasistical model selection based on Bayes decision theory. At first, we shall formulate the change detection problem based on Bayes decision theory. In this formulation, we introduce the general loss function for the practical problems. Moreover, we analyze the upper bound of the error rate of the model selection.

    CiNii J-GLOBAL

  • Based on Bayesian Statistics the Computational Learning Model and its Learnability

    NAKAZAWA Makoto, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Theoretical foundations of Computing   97 ( 157 ) 71 - 78  1997.07

    　View Summary

    In the PAC learning model and the U-learning model, the learning algorithm runs independent of the prior distribution. On the other hand, the Bayes algorithm works utilized the prior distribution, and it is Bayes optimal. Haussler have analyzed the sample complexity on the Bayes algorithm. But the algorithm usually requires a large amount of the time complexity. In this paper, we discuss on the complexity of the Bayes algorithm focusing on not only the sample complexity but also the time complexity. In this new learning model, the complexity depends on both the concept class and the family of priors. On the basis of both complexities, we propose a new concept called Bayesian learnability. Moreover we show the learnability of typical concept classes, and the properties of the Bayesian learnability.

    CiNii J-GLOBAL

  • A Formulation and Optimization of Data Retrieval Upon the Statistical Decision Theory

    KAJI Mio, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    人工知能学会全国大会論文集   11   225 - 228  1997.06

    CiNii J-GLOBAL

  • Mathematical model for key search by hashing, and asymptotic evaluation on efficiency of search

    FUTAGAMI Tsuneji, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   97 ( 80 ) 79 - 84  1997.05

    　View Summary

    In this study, an algorithm in which records stored in secondary storage by hashing are efficiently searched is proposed. Keys inherent to records and a quary are represented by binary vectors, and records having keys close to a quary in the Hamming space are searched. The search for all records leads to large access time to secondary storage. In this study, an algorithm was proposed that a vector representing a key of a record are divided into some blocks, and Hamming distances between a record and some code words in each block are stored in RAM. The condition that a number of searched records decreases in the proposed method compared with the previous method is found when the length of a vector is large enough.

    CiNii J-GLOBAL

  • On Clarke and Barron's Asymptotics of Bayes Codes

    GOTOH Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   96 ( 494 ) 73 - 78  1997.01

    　View Summary

    The Bayes code is the Bayes optimal solution based on Bayes decision theory. This is the method which uses mixture of all models in model class for coding function. B.S.Clarke and A.R.Barron analyzed asymptotic mean codelength of the Bayes code and showed that Jaffreys' prior is the asymptotically least favorable under entropy risk for i.i.d sources. This paper consists of two parts. At first, we show the asymptotic codelengths of the Bayes codes for individual sequences for the parametric model class. The main condition required here for the parameter space is that the posterior probability of parameter has asymptotic normality. Generally speaking, the asymptotic notmality of posterior distribution distribution holds for other than i.i.d. sources. Secondly, we shall prove that Clarke and Barron's asymptotics of the Bayes code is satisfied for more general model classes than i.i.d. sources. The main conditions required here is the Central Limit Theorem for the maximum likelihood estimates. Since the target of source coding is not usually i.i.d. source, the extension is this paper is effective.

    CiNii J-GLOBAL

  • Efficiency improvement of the concept learning using resemblence of attribution value.

    李相協, 松嶋敏泰, 平沢茂一

    日本経営工学会春季大会予稿集   1997  1997

    J-GLOBAL

  • 未知パラメータを含むマルコフ決定過程における学習アルゴリズムの提案

    前田 康成, 浮田 善文, 松嶋 敏泰, 平澤 茂一

    第19回情報理論とその応用シンポジウム予稿集     597 - 600  1996.12

  • 豊田秀樹著 : 非線形多変量解析 : ニューラルネットによるアプローチ, 朝倉書店(1996)

    松嶋 敏泰

    人工知能   11 ( 6 ) 970 - 970  1996.11

    DOI CiNii

  • On Bayes Coding in the case of limited memories

    NOMURA Ryo, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   96 ( 161 ) 31 - 36  1996.07

    　View Summary

    Recently, Bayes Coding is one of the most active subject in the research of universal coding. Bayes Coding is constructed based on statistic decision theory, and it determines the coding probability in the point of minimization of mean redundancy. Though, in the Bayes Coding algorithm for FSMX sources, the coding probability is calculated using a context tree it needs enormous memories. In this paper, first we show the lower bound of mean code length in limited memories. Secondly, we propose Bayes Coding algorithm under limited memories, and investigate its performance.

    CiNii J-GLOBAL

  • A Study on Error Probability of Statistical Model Selection

    NAKAO Takashi, GOTOH Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   96 ( 161 ) 7 - 12  1996.07

    　View Summary

    The statistical model selection is an important problem in the data analysis and learning theory AIC, MDL and BIC are the convensional information criteria for model selection. In this paper, we shall consider the model selection for the binary tree models which represents the relation between the attributes and class, and apply Bayes decision theory to the model selection. The convensional loss function is 0-1 loss and the Bayes risk of this loss represents the error probability of model selection. We propose the new loss function which define the distance between models. This criterion has the asymptotic property of consistency same as the maximum posterior probability criterion. We show the property of the proposed algorithm through the simulation experiment.

    CiNii J-GLOBAL

  • On Complexity of Decoding Beyond the BCH Bound Using Berlekamp-Massey Algorithm : An Application for Soft-Decision Decoding Using Algebraic Decoder

    KOBAYASHI Manabu, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   96 ( 161 ) 55 - 60  1996.07

    　View Summary

    If we use the conventional bounded distance decoding algorithm for Reed-Solomon codes or binary BCH codes, we offen cause the detection of errors. We can improve the probability of decoding error if we can find a codeword that is the most closest from the recieved word. R.E.Blahut has proposed a method for decoding beyond the BCH bound by continuing Berlekamp-Massey algorithm. In this paper we show the complexity of error and erasure decoding beyond the BCH bound. Furthermore, we introduce this method to soft-decision decoding and show that the complexity and the probability of decoding error of soft-decision decoding is reduced.

    CiNii J-GLOBAL

  • A study of Ziv-Lempel Algorithm from the view point of Bayes Code

    KAKU Nikkou, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   96 ( 161 ) 37 - 42  1996.07

    　View Summary

    Ziv-Lempel algorithm and Bayes algorithm are wellknowm as universal code. In recent years it is obvious that Ziv-Lempel algorithm supposes the probability distribution of information source implicitly. The relation between ZL code and Bayes code has been discussed from some three points of view[2]. From previous reseaches it is known that Bayes code surpasses ZL code concerning compresion rate. On the other hand ZL code surpasses Bayes code concerning complexity. So in this paper, from the three points of view, we consider the relation between ZL code and Bayes code by introducing the experimental algorithm.

    CiNii J-GLOBAL

  • 特集にあたって—特集 統計モデル選択

    松嶋 敏泰

    オペレーションズ・リサーチ = Communications of the Operations Research Society of Japan : 経営の科学   41 ( 7 ) 366 - 368  1996.07

    CiNii

  • A Note on Learning Uncertain Concept with Membership Queries.

    浮田善文, 松嶋敏泰, 平沢茂一

    人工知能学会全国大会論文集   10th   75 - 78  1996.06

    J-GLOBAL

  • On coded ARQ schemes cumulating the rejected sequences for very noisy channel

    NIINOMI Toshihiro, MATSUSIMA Tosiyasu, HIRASAWA Sigeichi

    IEICE technical report. Information theory   96 ( 53 ) 7 - 12  1996.05

    　View Summary

    Some AQR strategies, which do not discard the received sequences to be rejected have been proposed. The typical schemes of them are code combining, type2-AQR and so on. These kinds of ARQ make use of the rejected sequences for decoding the next sequence sent by the repeat request. In this paper, we extend the type1-ARQ proposed by Forney[5] to that of type2 naturally, and then analyze it. First, we show the result that the power of the test in ARQ scheme becomes increased by the retransmissions. Secondly, we show it possible to design the ARQ scheme of finite retransmissions for the worst case.

    CiNii J-GLOBAL

  • An Analysis on Difference of the Codelengths between Codes Based on MDL Principle and Bayes Codes

    GOTOH Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   96 ( 53 ) 13 - 18  1996.05

    　View Summary

    The minimum description length (MDL) principle which was proposed by J.Rissanen has been studied not only in the universal source coding but in the areas on data analysis, learning theory and the statistical model selection. The MDL is the method to minimize the total description length of the data and that of a probabilistic model, and is closely related to Bayesian statistics. This is because the MDL assumes implicitly the prior distribution. On the other hand, the Bayes coding is the method which uses mixture of all models in model class for coding function. The Bayes code is obtained by the Bayes optimal solution for the code length. Therefore, if we can assume the same prior distribution in both coding, it is clear that the Bayes code is superior to the code based on MDL principle. In this paper, we shall analysis the difference the codelengths between the MDL and the Bayes codes and show that the Bayes code is superior to the code based on the MDL principle.

    CiNii J-GLOBAL

  • Parallel Architecture for Signature Analyzer in LSI Self-Testing

    MATSUSHIMA Tomoko K., MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    Technical report of IEICE. ICD   96 ( 21 ) 85 - 92  1996.04

    　View Summary

    Several kinds of LFSR-based signature analyzers have been proposed for LSI built-in self test. MLFSR, which has been proposed for multiple output CUT by Pradhan et al., has the possibility to achieve the better aliasing probability than other schemes such as the multiple MISR scheme with comparable hardware complexity. The only problem with this scheme is that the hardware complexity becomes larger than propotionally as δ increases, where δ is the number of parallel signals inputted into MLFSR, and so MLFSR is not adequate for testing CUTs with large number of output signals. In this report, we propose a parallel architecture for signature circuits applicable to such CUTs. This architecture allows Hδ bits to be processed in parallel, where H can be chosen as an arbitrary integer. It is shown that the complexity for the parallel circuit, with Hδ input, signals is much smaller than that for a parallel opereation of H converntional circuits with δinput signals.

    CiNii J-GLOBAL

  • A consideration on learning of probability model in which length of code is evaluated.

    後藤正幸, 松嶋敏泰, 平沢茂一, 俵信彦

    日本経営工学会秋季研究大会予稿集   1996  1996

    J-GLOBAL

  • MDL principle and Bayesian theory in changing time detection of information source.

    後藤正幸, 松嶋敏泰, 平沢茂一, 俵信彦

    日本経営工学会春季大会予稿集   1996  1996

    J-GLOBAL

  • An Algorithm Learning Probabilistic Rules.

    峯松一彦, 松嶋敏泰, 平沢茂一

    人工知能学会全国大会論文集   10th  1996

    J-GLOBAL

  • Consideration about the Constructive Inductive Logic Programming.

    新津健, 浮田善文, 松嶋敏泰

    電子情報通信学会技術研究報告   AI95-47 ( 460(AI95 42-56) ) 41 - 46  1996.01

    J-GLOBAL

  • A Study on Parallel Encoder and Decoder for Cyclic Codes

    MATSUSHIMA Tomoko K., MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   95 ( 347 ) 23 - 28  1995.11

    　View Summary

    In this paper, a parallel encoder and decoder architecture for cyclic codes is presented. This architecture can decrease encoding and decoding time 1/H(H > 1) compared to conventional codec, where H is the number of symbols processed in parallel. As an example, we investigate hardware complexity for a (255,251) Reed-Solomon code over GF(2^8). It is shown that hardware complexity for a set of parallel encoder and decoder is much smaller than that for a parallel operation of H conventional sets.

    CiNii J-GLOBAL

  • 質問を許す概念学習に関する一考察

    浮田 善文, 松嶋 敏泰, 平澤 茂一

    第18回情報理論とその応用シンポジウム予稿集     537 - 540  1995.10

  • A Note on Learning Theory for Probabilistic Models

    後藤正幸, 松嶋敏泰, 平沢茂一

    情報処理学会全国大会講演論文集   51 ( 1 ) 19 - 20  1995.09

    CiNii J-GLOBAL

  • Optimum Learning Rules for Boolean functions based on Bayesian Statistics

    中沢真, 松嶋敏泰, 平沢茂一

    情報処理学会全国大会講演論文集   51 ( 3 ) 175 - 176  1995.09

    CiNii J-GLOBAL

  • Note on Maximum Likelihood Decoding of Linear Block Codes

    TAKAHASHI Ryo, KOBAYASHI Manabu, MATUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   95 ( 145 ) 55 - 58  1995.07

    　View Summary

    It is known that we regard the maximum likelihood decoding problem as a search through a trellis for linear block code. However a problem is to reduce complexity of search to execute MLD. On the other hand, there is decoding algorithm using acceptance criterion that codeword is maximum likelihood, too. These combination is known as efficient decoding. In this paper we propose efficient decoding using trellis by new acceptance criterion. Moreover we show that decoding complexity is reduced in the computer simulation.

    CiNii J-GLOBAL

  • A Study on Parameter Estimation and Ziv-Lempel Code

    KIMURA Masaru, GOTOH Masayuki, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   95 ( 145 ) 49 - 53  1995.07

    　View Summary

    Bayes coding is the optimal universal code with respect, to Bayes redundancy based on the prior distribution. On the other hand, it was shown that Ziv-Lempel coding is equivalent, to the coding by estimated parameter whose type is Laplacean. However, this discussion was under the ideal condition. In this paper we assume that, the Ziv-Lempel code is equivalent, to the code by Laplace estimator and exmamine the parameter of Laplace estimator which is equivalent to the parameter of the prior distribution though the simulation expriments. We show that a plactical Ziv-Lempel code is nearly equivalent to the code by Laplace estimator based on the only a prior.

    CiNii J-GLOBAL

  • An Idea In The Field Of Markov Decision Processes With Unknown Transition Probabilities

    MAEDA Yasunari, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   95 ( 145 ) 25 - 30  1995.07

    　View Summary

    In this paper, we propose a new algorithm in the field of markov decision processes with unknown transition probabilities. The decision algorithms are evaluated by only a criterion of convergence or rewards in previous researches. The proposed algorithm is considered from both criteria. The effectiveness of our algorithm against previous algorithm is shown by some simulations.

    CiNii J-GLOBAL

  • A Test for Psuedo-Random Numbers Using the Bayes Coding

    BAMBA Masakazu, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   95 ( 145 ) 37 - 42  1995.07

    　View Summary

    The most useful method to get some randomness in computational simulation is to use psuedo-random numbers. This paper gives a new approach, using Bayes Coding Algorithm. The proposed method tests some traditional tests at once. This paper comes from the Information Theory, likes a test using Lemple-Ziv algorithm. But, we test not only redundancy. Our test, using Bayes Coding Algorithm, can also analize the probability of each sequence.

    CiNii J-GLOBAL

  • Lossy Compression using String Matching

    OBATA Hiroaki, KOBAYASHI Manabu, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   95 ( 145 ) 43 - 48  1995.07

    　View Summary

    There is a lossy compression algorithm using string matching in LZ77 code. But LZ77 code has many redundancy to improve. So, instead of LZ77 code, we use Fiala-Greene code to realize an efficient compression. Morever we show the effectiveness of the proposed algorithm by simulation.

    CiNii

  • A study of data compaction by Bayes Coding

    SHIMIZU Atsushi, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   95 ( 145 ) 31 - 36  1995.07

    　View Summary

    Among the universal coding problems, Bayes Coding is one of the most active subject in the research field of recent data compaction. The Bayes Coding Algorithms for FSMX sources proposed in the recent researches use a fixed-depth context tree. In this paper, we study the compression ratio of the newly proposed algorithm which uses a variable-depth context tree, and investigate the difference of redundancy caused by prior probability distribution of prameters.

    CiNii J-GLOBAL

  • A Bayes coding algorithm for Markov models

    MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    IEICE technical report. Information theory   95 ( 79 ) 1 - 6  1995.05

    　View Summary

    The optimal universal code for FSMX sources with respect to Bayes redundancy criterion is deduced under the condition that the model, the probabilistic parameters and the initial state are unknown. The efficient algorithm of the optimal code is also proposed by using a context tree. Although the context tree weighting(CTW) algorithm needs the context in the initial situation and can not treat the infinite depth context tree, this algorithm is free from these problems. The algorithm is not only Bayes optimal for FSMX sources but also asymptotically optimal for a stationary ergodic sources. Moreover the algorithm is regarded as a generalization of the Ziv-Lempel algorithm.

    CiNii

  • 確率モデルの学習に関する一考察

    後藤正幸, 松嶋敏泰, 平沢茂一, 俵信彦

    日本経営工学会秋季研究大会予稿集   1995  1995

    J-GLOBAL

  • A Note on Inductive Learning of Probabilistic Model

    Abe Shinji, Mukouchi Takafumi, Matsushima Toshiyasu, Hirasawa Shigeichi

    IEICE technical report. Information theory   94 ( 171 ) 43 - 48  1994.07

    　View Summary

    This paper discusses an inductive learning method in probabilistic model which is applied to diagnostic system.In this system empirical knowledge is learned from given data as the probability distribution of the failures,and tests are selected according to this knowledge.We use presumption tree to represent the probability distribution,and adopt the MDL principle to select a presumption tree as themost approximate one.But,since the probability distribution becomes complicated,complexity of model selection increases exponentially with number of attributes So it requires an effcient search technique. In this paper,we propose a new effcient algorithm to search the optimal presumption tree which minimize it′s description length.An d we show that our algorithm gives a supplement of the weakness of the conventional algorithm.

    CiNii J-GLOBAL

  • A Note on the Construction Method of Decision Trees.

    Umezawa Katsuyuki, Niinomi Toshihiro, Matsushima Toshiyasu, Hirasawa Shigeichi

    IEICE technical report. Information theory   94 ( 171 ) 49 - 54  1994.07

    　View Summary

    The technique which derives a general rule to explain the given examples called an inductive learning.In this paper,we discuss on the decision tree as a method for the expressing the knowledge obtained by learning though there are various forms such as the formal.language,the predicate logical expression,and PROLOGprogram. The ID3 is proposed by J.R.Quinlan as a method for constructing the decision t e.However the correlation of two or more attributes can not take into account.because only one attribute paid attention in each step of the generation process of the tree.As a result,it is not guaranteed that the average number of questions using the generated rule is minimized.We propose a new algorithm which enables to consider the relationship between two or more attributes in each step of the generation process of the tree.And it is shown a more efficient decision tree can be constructed.

    CiNii J-GLOBAL

  • On the Complexity of Hypothesis Space and the Sample Complexity for Machine Learning

    Nakazawa Makoto, Matsushima Toshiyasu, Hirasawa Shigeichi

    IEICE technical report. Information theory   94 ( 171 ) 37 - 42  1994.07

    　View Summary

    The problem of learning a concept from examples in the model introduced by Valiant is discussed.According to the traditional ways of thinking,it is assumed that the learnability is independent of theoccurence probability qf instance.By utilizing this probability,we propose the metric as a new measure to determine the complexity,of hypothesis space.The metric measures the hardness of discrimination between hypotheses. Furthermore,we obtain the average metric dependent on prior information.This metric is the measure of complexity for hypothesis space in the average.Similarly in the worst case,we obtain the minimum metric. We make clear the relationship between these measures and the Vapnik-Chervonenkis(VC)dimension.Finally,we show the upper bound on sample complexity utilizing the metric.This results can be applied in the discussion on the learnability of the class with an infinite VC dimension.

    CiNii

  • A Note on Update of Uncertain Knowledge

    Kawamata Hidenori, Nakazawa Makoto, Matsushima Toshiyasu, Hirasawa Shigeichi

    IEICE technical report. Information theory   94 ( 171 ) 55 - 60  1994.07

    　View Summary

    In the research area on knowledge information processing, knowledge acquisition from experts becomes an important problem to construct efficient expert systems.On the other hand,the method for learning rules from examples is also important.Using rules given from a finite set examples,we should represent uncertain knowledge with range of certain factors.If we can combine knowledge given from experts with knowledge given from examples,we can establish more reliable knowledge.In this paper,we propose a new method that update the knowledge based on experts by using examples,provided that additional examples have noises in the observation.

    CiNii J-GLOBAL

  • INDUCTIVE AND DEDUCTIVE INFERENCE BASED ON INFORMATION THEORY

    Hirasawa Shigeichi, Matsushima Toshiyasu

    IEICE technical report. Information theory   94 ( 145 ) 73 - 85  1994.07

    　View Summary

    A fundamental and total model for deductive and inductive inference is proposed from the view points of decision theory and information theory.Deductive and inductive inference are regarded as the decision problems in the proposed fundamental model.The inference problems of induction and deduction are represented by the decision functions and the loss functions.The optimal procedures of the inference problems are given by decision theory. The average risks of the optimal procedures are evaluated by using information theory.

    CiNii

  • On an Uncertain Knowledge Representation Using a Certainty Factor and a Confidence Factor and its Reasoning Algorithum

    SATO Jun-ichi, MATSUSIMA Toshiyasu, HIRASAWA Shigeichi

    人工知能学会全国大会論文集   8   25 - 28  1994.06

    CiNii J-GLOBAL

  • An Inference from a Contradictory Knowledge

    SAITO Mikiya, MATSUSHIMA Toshiyasu, HIRASAWA Shigeichi

    人工知能学会全国大会論文集   8   63 - 66  1994.06

    CiNii J-GLOBAL

  • An Efficient Procedure of Inductive Learning for PROLOG.

    浮田善文, 松嶋敏泰, 平沢茂一

    人工知能学会全国大会論文集   8th   137 - 140  1994.06

    J-GLOBAL

  • On coded ARQ schemes cumulating the rejected sequences

    Niinomi Toshihiro, Matsushima Toshiyasu, Hirasawa Shigeichi

    IEICE technical report. Information theory   94 ( 35 ) 37 - 42  1994.05

    　View Summary

    On ARQ schemes,using VA(Viterbi algorithm)and cumlating the rejected sequences to make use to the powerful decision for the next repeated,it is one of approaches that eliminating only the non-reliable segments from maximum likelihood path over the trellis block,chosing by the likelihood ratio testing at the each two pathes unmerged.Then,the decoder selects the only rebable segments form each blocks repeat requested.On these cases,the procedure of VA with some earsure option is not the single stage testing like Yamamoto￡1!′s scheme,but the sequntal tesing problem s.In this paper,we disccus the sequential testing,espacially using VA with repeat request the rejected sequences cumulating. ￡1!H.Yamamoto and K.Itoh,″ Vitebi decoding algorithm for convol utional codes with repeat request″ IEEE Trans.Inf.Theory,vol.IT-26 ,pp540-547(Sep.1980).

    CiNii J-GLOBAL

  • On block coded ARQ schemes cumulating the rejected information

    Niinomi Toshihiro, Matsushima Toshiyasu, Hirasawa Shigeichi

    IEICE technical report. Information theory   93 ( 164 ) 101 - 106  1993.07

    　View Summary

    The ARQ is an error control scheme such that,if the receiver decides that the received information is not reliable,he can request the same information repeated.Some kinds of ARQ schemes do not disacard non-reliable informaion,but cumulating it to make use of powerful decision if the next received sequence should be decoded or not.This idea can be considered as a sequential decision with the cumulating rejected information.The well-Known Wald′s sequntial ratio test,which can make most powerful decision if sample size is variable,have the same principle like these kinds of ARQ.In this paper,we try to evaluate the ARQ cumulating rejected information with the random coding argument like Forney￡7 !′s as possible.So we study the error exponent of decoding the 2nd inform under the condision of the 1st inform is rejected.

    CiNii J-GLOBAL

  • On Reasoning Systems with Computed Range of Certainty Factors.

    鈴木誠, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   92 ( 56(IT92 1-10) )  1992

    J-GLOBAL

  • A Note on Problem of Knowledge Acquisition.

    阿部健一郎, 松嶋敏泰, 平沢茂一

    人工知能学会全国大会論文集   6th ( Pt 2 )  1992

    J-GLOBAL

  • On minimax redundancy distortionless codes for finite sequences.

    松嶋敏泰, 稲積宏誠, 平沢茂一

    電子情報通信学会技術研究報告   91 ( 256(IT91 52-61) )  1991

    J-GLOBAL

  • Strategies for Maximizing Mutual information from Viewpoint of Knowledge Acqusition.

    鈴木譲, 松嶋敏泰, 稲積宏誠, 平沢茂一

    電子情報通信学会技術研究報告   91 ( 161(IT91 31-39) )  1991

    J-GLOBAL

  • A Note on Inference of Uncertain Knowledge.

    鈴木誠, 野村明子, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   91 ( 162(IT91 40-51) )  1991

    J-GLOBAL

  • Path memory truncation on the Viterbi algorithm with decision feed back.

    新家稔央, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   89 ( 432(SP89 124-130) )  1990

    J-GLOBAL

  • A note on selection for grammatical inference.

    野村明子, 川又俊史, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   90 ( 152(IT90 33-51) )  1990

    J-GLOBAL

  • On the viterbi algorithm with decision feed back. Path memory truncation on the viterbi alogorithm with decision feed back.

    新家稔央, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   90 ( 234(IT90 52-59) )  1990

    J-GLOBAL

  • A note on applications of coding with distortion for ZL coding scheme.

    松岡文啓, 中篠健, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   90 ( 152(IT90 33-51) )  1990

    J-GLOBAL

  • Notes on structure of quick-look-in codes.

    山田吉康, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   89 ( 432(SP89 124-130) )  1990

    J-GLOBAL

  • 情報理論に基づく推論の体系化と不確実な知識表現への応用

    松嶋 敏泰, 鈴木 譲, 稲積 宏誠, 平澤 茂一

    日本経営工学会誌   40 ( 3 ) 196 - 196  1989.08

    CiNii

  • A note on knowledge representation in hypothesis-based reasoning.

    川又俊史, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   89 ( 145(IT89 22-33) )  1989

    J-GLOBAL

  • On a formulation of inductive inference from the view point of source coding.

    松嶋敏泰, 鈴木譲, 稲積宏誠, 平沢茂一

    電子情報通信学会技術研究報告   89 ( 61(IT89 1-10) )  1989

    J-GLOBAL

  • On systemization of inference based on information theory.

    松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   89 ( 324(IT89 68-71) )  1989

    J-GLOBAL

  • A note on efficient ARQ scheme.

    新家稔央, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   88 ( 139 )  1988

    J-GLOBAL

  • Feature ordering & stopping rule based on maximizing mutual information=pattern’s focusing.

    鈴木譲, 松嶋敏泰, 稲積宏誠, 平沢茂一

    電子情報通信学会技術研究報告   88 ( 139 )  1988

    J-GLOBAL

  • Stopping rules for pattern recognition. Comparison with DP search method.

    鈴木譲, 松嶋敏泰, 稲積宏誠, 平沢茂一

    電子情報通信学会技術研究報告   87 ( 51 )  1987

    J-GLOBAL

  • The modified associative memory by using the weight of data.

    貞重勝也, 松嶋敏泰, 稲積宏誠, 平沢茂一

    電子通信学会技術研究報告   86 ( 300 )  1987

    J-GLOBAL

  • A new scheme of the control method for CSMA/CD to avoid re-collision.

    にな川浩幸, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   87 ( 120 )  1987

    J-GLOBAL

  • A study on feather of threshold decoding.

    岡本文孝, 松嶋敏泰, 鈴木譲, 平沢茂一

    電子通信学会技術研究報告   86 ( 301 )  1987

    J-GLOBAL

  • A study on evaluation of inference from information theory.

    松嶋敏泰, 鈴木譲, 稲積宏誠, 平沢茂一

    電子情報通信学会技術研究報告   87 ( 51 )  1987

    J-GLOBAL

  • A note on quantitative evaluation of reasoning algorithms.

    榎本孝志, 稲積宏誠, 松嶋敏泰, 平沢茂一

    電子通信学会技術研究報告   86 ( 300 )  1987

    J-GLOBAL

  • Notes on the decoding complexity for concatenated codes.

    楠本和哉, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   87 ( 134 )  1987

    J-GLOBAL

  • Studies on uncertanty logic for default reasoning.

    松嶋敏泰, 鈴木譲, 稲積宏誠, 平沢茂一

    電子情報通信学会技術研究報告   87 ( 120 )  1987

    J-GLOBAL

  • A note on a new slotted ring system used for voice and data switching.

    新倉陽子, 松嶋敏泰, 平沢茂一

    電子情報通信学会技術研究報告   87 ( 134 )  1987

    J-GLOBAL

  • Stopping rule for pattern recognition.

    鈴木譲, 松嶋敏泰, 稲積宏誠, 平沢茂一

    電子通信学会技術研究報告   86 ( 285 )  1986

    J-GLOBAL

  • A note on statistical data from the viewpoint of information theory. Parameter estimation for sampling inspection.

    鈴木譲, 松嶋敏泰, 稲積宏誠, 平沢茂一

    電子通信学会技術研究報告   86 ( 29 )  1986

    J-GLOBAL

  • A study of discrete data information structure model.

    松嶋敏泰, 鈴木譲, 稲積宏誠, 平沢茂一

    電子通信学会技術研究報告   86 ( 285 )  1986

    J-GLOBAL

  • A study of a multinomial distibution control chart by m-information.

    松嶋敏泰, 池沢たつ夫

    日本品質管理学会年次大会講演・研究発表要旨集   14th  1984

    J-GLOBAL

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Syllabus

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Overseas Activities

  • 多端子情報理論の基礎となる新たな基礎数理の構築

    2011.04
    -
    2012.03

    アメリカ   University of California Berkeley

  • ベイズアプローチによる学習理論と事後確率の効率的計算アルゴリズム

    2001.10
    -
    2002.07

    アメリカ   ハワイ大学

Sub-affiliation

  • Faculty of Science and Engineering   Graduate School of Fundamental Science and Engineering

Research Institute

  • 2024
    -
    2026

    Waseda Research Institute for Science and Engineering   Concurrent Researcher

Internal Special Research Projects

  • ユーザの情報秘匿可能な分散符号化方式の理論基盤構築及び情報理論的総合性能評価

    2024  

    　View Summary

    ユーザが保管したい情報（秘密）に乱数を交えて符号化して，複数のストレージにその一部（シェア）を保存することで，秘密が何であるかを各ストレージに秘匿しつつ，かつ一部のシェアが消失しても秘密を復元可能にする情報保管方式の一つである秘密分散方式を応用し，検索クエリに乱数を交えて符号化して，複数の検索サーバにその一部を送信することで，ユーザの検索対象が何であるかを各検索サーバに秘匿可能にする情報検索方式の一つである「プライバシー保護情報検索」(PIR)において新しい方式を提案した．従来研究では，検索サーバの応答値のデータ量が理論的に最小である評価が重要視されたきたが，本研究では，データ量，情報処理の際の計算時間およびメモリ量を総合的に評価したもとで，データが誤った/消失した場合の復元能力なども有する方法をいくつか提案した．

  • 効率性，信頼性，情報秘匿性を有する分散蓄積・計算・通信方式の基礎理論構築

    2023  

    　View Summary

    ユーザの検索対象が何であるかを各計算機に秘匿したまま情報検索を可能とする方式の一つである「プライバシー保護情報検索」に関する研究においては，MDS符号を用いた秘密分散方式を利用して新方式の提案を行った．この方式が計算量やある種の通信レートにおいて従来研究より優れていることを理論的に示すとともに，数値計算でもその特性を示した．また，この方式を拡張して，サーバーからの情報が消失したり，サーバーが意図的に情報を改ざんした場合にも対応できる方式も提案し，性能評価も行った．計算データの誤り，消失を訂正可能であるという計算における信頼性を有しつつ，計算対象が何であるかを各計算機に秘匿したまま高効率な計算を可能とするデータ処理方式の一つである「分散符号化計算方式」の構成に関する研究においては，サーバーをグループ化した方式において，消失や改ざんに対して従来研究と同等の訂正性能を持ちながら，計算効率が高い新方式を提案し，その特性を理論的に解析しその有用性を証明した．

  • 効率性，信頼性，秘匿性を考慮した分散符号化計算方式の理論基盤構築

    2022  

    　View Summary

    複数の計算機を用いることで，計算データの誤り及び消失を訂正可能であるという計算における信頼性を有しつつ，高効率な計算を行うデータ処理方式の一つである「分散符号化計算方式」，及び，ユーザが計算したい対象が何かを各計算機に秘匿したまま計算を可能とする機能も備えた「分散秘匿符号化計算方式」の構成法を研究し，次の成果を得たので，10月の国際会議にて公開した．(1)有限体上の巨大な行列A,Bの積行列ABの計算における，誤り，消失訂正と計算時間を考慮した分散符号化計算方式の提案．(2)上記に加え，行列Aの値を計算機に秘匿する機能も有する分散秘匿符号化計算方式の提案．さらに，両方式の性能評価も行い，その有効性を確認した．

  • 情報理論的完全情報秘匿のもと最適な効率性を有する秘匿情報検索方式の理論基盤構築

    2021  

    　View Summary

    本研究の目的は，ユーザが複数のサーバを利用することで，ユーザが何を検索したいかという情報を完全に秘匿しながら情報検索を行う「プライバシー情報保護検索方式」（Private Information Retrieval, PIR）のうち，高い効率性を有する方式の一般的な構成法に関する理論基盤の構築である．成果の一つとして，次のものが挙げられる：現実的に妥当な仮定を設けたうえで，そのようなPIRの満たすべき条件を線形代数的，さらに有限射影幾何的に再定式化したうえで，それらの条件を満たす方式の構成アルゴリズムを構築した．本成果は2021年5月の日本経営工学会春季大会にて公開された．

  • 情報理論的完全情報保護のもと効率的かつ信頼性が高い分散計算システムの理論基盤構築

    2020  

    　View Summary

    本研究の目的は，情報理論的に完全に情報を保護したもとでの高信頼性を有する高効率な分散計算システムの理論基盤を構築することである．本研究では，効率性，安全性，秘匿性を考慮した分散処理システムを数理的に定式化し，各評価基準の最適値のトレードオフ解析を行い，最適性を達成する分散計算システムを構築する手法を採用した．成果の一つとして，情報理論的に完全にプライバシ保護したもとでの通信の効率が最適である情報検索システムと，サーバの情報が他サーバの情報から最適な効率で復元可能な分散ストレージシステムの対応関係を，集合等の記法を用いて簡明に整理したことが挙げられる．本成果は3月の情報理論研究会にて公開された．

  • 高信頼性, 高安全性を有する高速な分散処理システムの研究

    2019  

    　View Summary

    近年，個人情報を含むビッグデータが増え，そのようなデータを処理するシステムが求められている．その際，データを盗聴者から安全に保護しつつ処理するという安全性，高速に処理を行うという計算処理時間，処理の際に誤りが起こっても正確に処理できるという信頼性，という3つの評価基準が重要になる．従来は，データを分散してから処理することにより，いずれかの評価基準において良くなるようなシステムが研究されてきた．例えば，データを複数のサーバに分散し並列処理を行うことで高速に信頼性の高い処理を行うというcoded computationや，データを複数のストレージに分散することで安全に保護するという分散ストレージがある．これらは，数理モデルを定式化することで厳密に議論されてきた．しかし，すべての評価基準を考慮に入れたシステムに関しては，現在十分な研究があるとは言えない．本研究は，coded computation に分散ストレージに関する理論を取り入れることで，高信頼，高安全性を有する高速な分散処理システムの理論を確立を目指した．具体的には，単純に組み合わせるのではなくシステム全体について厳密に議論するため，システム全体の数理モデルを定式化し，性能の評価基準を明確に定義し，その下で性能の理論限界を導出し，それを達成するシステムを構築した．

  • ネットワーク知能の基礎数理モデルに向けた情報理論の拡張

    2017  

    　View Summary

    ネットワーク知能とも呼ぶべき近年の人工知能における，推論，学習の最適性や理論限界を明確にするための基礎理論構築に向けた情報理論の拡張および，ネットワーク上で相互に通信を行いながら所望の推論結果を得るための通信アルゴリズムに関する研究を行った．情報理論の拡張としては特に，歪みのある情報源符号化における理論限界の導出を行った．また，可変長intrinsic randomness問題における様々な理論限界の導出および，それらと他の情報理論の問題における理論限界との対応関係を明らかにした．通信アルゴリズムに関する研究としては特に，ランク誤りを考慮したcoded computationのための通信アルゴリズムを提案した．

  • ネットワークデータ処理のためのスパースモデリングの拡張と数理基盤の構築

    2016  

    　View Summary

    スパースモデリングによるビッグデータ解析の研究は多くの成果を収めているが，その範囲はデータの解析部分がほとんどで，解析に至るまでの収集，蓄積，検索，通信等のネットワークデータの処理プロセス全体についてはほとんど考察されていない．また，解析を中心とした研究では評価基準として解析精度のみに注目した考察で十分であったが，通信量，蓄積量等の効率の評価基準や情報保護，漏洩情報量等の安全性の評価基準を同時に考察することが必要となる．そこで，本研究では，ネットワークデータの収集，分散蓄積，分散解析の３つの処理プロセスに対して，数理モデルによる問題のモデル化と評価基準の数理的定義を行ない，問題の定式化と解くべき問題を整理した．その後，それらの問題に対して最適なあるいは近似最適なアルゴリズムの構成やその性質の理論的考察を行なった．さらに，アルゴリズムの実装と実験による性能評価を行なった．

  • ベイズ符号による無歪み画像圧縮に関する研究

    2013  

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    　従来の無歪画像圧縮に関する研究は，アドホックな方法によるアルゴリズムの開発と，試行錯誤を繰り返すことによるアルゴリズムの改良というアプローチを採っており、理論的最適性などが保証されていることはあまりない．これらの研究は，この根本的問題を解決しない限り，画像圧縮の研究が大きな進展を得ることは期待できない．これに対し，本研究ではまず，画像に対して適した確率モデルを構築し，その確率モデル上で最適性を保証するベイズ符号を構成するアプローチをとることで，上記の根本的問題の解決を試みるものである． まず，本年は研究目的のため，画像データには特化せず，より基本的な情報源を考え，ベイズ符号やベイズ符号を用いた予測についての理論的な解析と画像データの確率モデルの基礎となるいくつかの確率モデルに対して，最適または近似最適な効率的なアルゴリズムの構成とその性能評価をおこなった．(1) 真のモデルとベイズ符号が仮定したモデルの符号長における影響の漸近解析　ベイズ符号は，パラメタライズされた分布を仮定しその確率パラメータを未知としてベイズ基準で符号長最小の符号化となっているが，もし仮定した分布で真の分布が表現できない場合，ベイズ基準の意味での最適性は保証されない．しかし，真の分布と仮定した分布の中でK-L情報量的に最も近い分布とのK-L情報量だけ漸近符号長が長くなるものの，ベイズ符号が優れた性質もつことを証明した．　特に，画像データのように階層的な確率モデルが仮定される場合に，真の画像データの分布がその仮定した階層確率モデル族で表現できない場合でも，階層モデルの中で，平均符号長を最小とするモデルに漸近収束することが示され，真の分布を，仮定した確率モデルが含まない場合でも，ベイズ符号が優れた性質を持っていることを示した．(2) ベイズ符号のオーバーフロー確率の理論評価　ベイズ符号が平均符号長を評価基準としてベイズ基準，minimax基準，maxmin基準において漸近的に最適な符号であることはよく知られているが，オーバーフロー確率の面での評価は今までに行なわれていなかった．実用的な見地からは，平均符号長における評価のみならず，符号長が，あるメモリー量をオーバーしてしまう確率であるオーバーフロー確率も重要な評価指標である．そこで，符号長の２次モーメントや自己エントロピーの２次モーメントを用い，オーバーフロー確率の漸近解析を行なった．その結果この面においてもベイズ符号が優れた特性を有することが示された．(3) 文脈木モデル以外の拡張された情報源に対するベイズ符号アルゴリズムの構築　情報源符号化の研究の多くは，情報源の確率的な性質は時間によって変化しないとする定常情報源を対象としている．文脈木モデルも例外ではない．ところが，実データにおいては，幾つかの性質が異なるコンテンツが1つのファイルに含まれていることも多く，そのようなファイルを情報源として見た場合には，非定常な情報源と考えるのが自然である．情報源が非定常であるにも関わらず，定常情報源の場合と同様の符号化アルゴリズムを使用すれば，良い圧縮性能を望むことは出来ない．情報源が非定常であれば，符号化アルゴリズムもその変化を追従するアルゴリズムを構築する必要がある．一言に非定常情報源と言っても，モデル化の方法は一意ではなく，幾つかのモデルが考えられる．本研究グループは，これらのモデルの内の一部である区間で定常な非定常情報源やパラメータが時間によって変化する文脈木情報源に対するベイズ符号を提案し，性能に関する理論解析を行い，さらにベイズ符号を実現する効率的アルゴリズムを提案した． 　また，実データに対する符号化を考えると，データのサイズが小さい場合には，全種類の情報源アルファベットが出てこない場合が考えられる．このような場合に，従来と同様の符号化をしてしまうと，圧縮の性能が劣化してしまうことが知られている．本研究グループは，情報源アルファベットの出現パターンを考慮した情報源モデルに対するベイズ符号を提案し，性能に理論解析を行い，さらにベイズ符号を実現する効率的なアルゴリズムを提案した．　それらの研究の拡張として，画像データや言語データ等にも適した非定常な情報源モデルや情報源アルファベットが部分的に出現する情報源モデルの検討を行い，ベイズ符号の性能に関する理論解析及び，ベイズ符号を実現する効率的アルゴリズムの構築を行った．

  • 確率推論アルゴリズムに基づいたストリーム暗号への統一的攻撃法安全性に関する研究

    2009  

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    従来のストリーム暗号の研究では，非線形コンバイナ型乱数生成器の高速攻撃法の一部で通信路符号化の高効率復号アルゴリズムが応用されていたが、攻撃を確率推論の問題としてモデル化したもとで攻撃法を解析した研究は存在しなかった。また、暗号の安全性研究の多くは、それぞれの暗号に対して個別の攻撃法の提案が行なわれ、それに基づき安全性評価が行なわれてきた。しかしこのようなアプローチでは、より強力な攻撃法が新たに提案される可能性が残り、安全性の保証が非常に不安定であった。本研究では、まず、非線形コンバイナ型のみならず全てのストリーム暗号に対する攻撃を確率推論の問題として定式化し統一的な枠組を構築した。次に、この統一的枠組のもとで、最適な攻撃法をベイズ決定理論から理論的に導出した。この最適解が明示されたことにより、非線形コンバイナ型のみならず、従来研究では効率的攻撃法が見いだせなかった様々な種類のストリーム暗号に対しても攻撃法を考察できるようになった。この最適解を求める（最適な攻撃を行なう）ためには、一般に乱数生成器の鍵の長さの指数オーダの計算量が必要であるため、効率的な確率推論アルゴリズムを適用することで莫大な計算量を削減する必要がある。そのため、本質的に同等な確率推論問題を扱っている周辺分野で、高い性能を有していることが実証されているアルゴリズム、例えば、符号理論や統計力学の分野で多く用いられている和積(sum-product)アルゴリズム等の応用を考察した。また、信号処理や実験計画の視点からのアルゴリズムについてもいくつか考察を行なった。その他として、基盤となるベイズ決定理論についても、様々な応用分野について広く考察し、最適または近似的に最適なアルゴリズムを導出することにより、ストリーム暗号への応用の基礎がためを行なった。さらに、乱数生成自体やそれと同質の問題である情報源符号化の問題に対しても、情報理論的視点からその限界に対する考察も行なった。

  • 大規模分散ネットワーク情報の処理に関する基礎モデルの構築と特性解析

    2006  

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    　ネットワーク上で分散して存在する膨大な情報をいかに処理するかは，今後ますます重要な問題となってくると考えられる．しかし，この分野では数理的基礎モデルが十分でなく，最適解や性能限界について議論がなされていないため，今後のこの分野における発展のための道標は明確とは言えない．　そこで本研究では，ネットワーク分散情報の処理における，実システムを視野に入れた，この分野における基礎理論の構築を目指す．数理的基礎モデルの構築から実際のアルゴリズム・システム設計までの段階的研究アプローチの一環として，まず基礎モデルの構築と，最適解や理論的性能限界についての定式化を目的としていた．大きくわけて以下の2つのステップに分けて研究を行った．①ネットワーク上に分散した情報の伝送と決定・制御に関する多端子情報理論と統計的決定理論を用いた基礎モデルを構築し，構築したモデル上で各問題の目的に応じた評価関数を定義し，最適解や理論的性能限界についての定式化を行う．②定式化した最適解またはその近似解を実現するアルゴリズムをグラフ上のメッセージ伝播アルゴリズム等を用いて設計し，その性能や計算量の評価を解析的・実験的に行う．

  • メディアネットワークにおける高圧縮符号化技術に関する研究

    2002  

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    多種多様な形態の情報が多量に伝送，蓄積される，ネットワーク情報化社会において，情報の圧縮技術は欠く事のできない基盤技術となりつつある．情報圧縮の符号化（情報源符号化）の領域は大別して次の2つがある．①無歪圧縮（元の情報系列に可逆的に戻るもの）②有歪圧縮（元の情報系列に可逆的に戻らないもの）本研究では主に①の無歪圧縮，特に無歪ユニバーサル符号化について扱った．情報源の確率構造が既知の場合はShannon-Fanoの符号化，Huffmanの符号化等を用いることにより理論的圧縮限界であるエントロピーまで圧縮可能なことはよく知られている．しかし，現実のテキスト，画像の情報系列はその情報源の確率構造が未知である場合がほとんどで，このような場合が無歪みユニバーサル符号化の問題である．現在無歪ユニバーサル符号化アルゴリズムとして広く実用化されているZiv-Lempel符号は定常エルゴード情報源に対し漸近的にエントロピーまで圧縮できる優れた符号であるが，その収束速度は遅く，最適でない事が知られている．そこに近年，無歪みユニバーサル符号の収束の速さの理論的限界がアメリカの研究者により明らかになると共にそれを達成する符号（例えばベイズ符号）が提案された．また，木構造を有効に用いた符号化のアルゴリズム(CTW法)もオランダの研究グループにより提案され，理論ばかりでなく実用化についても可能性が開けつつある．本研究グループも理論と符号化アルゴリズム両面でアメリカ，オランダの研究者たちとほとんど同時期に同様の成果を発表し，その後もこの研究を発展させている．しかし，これらのアルゴリズムは，計算量・メモリー量の面で問題があり，まだ実用的ではなかった．そこで，本研究では無歪みユニバーサル符号の計算量・メモリ量において実用的なアルゴリズムの構築を行い，理論的，実験的にその性能の解析および評価を行った．また，情報源が時系列的に変化する場合のユニバーサル符号の提案を行い，その最適性の証明及び実験による評価も行った．さらにこの研究の拡張として，このベイズ的に最適なユニバーサル符号を信号処理や分散協調処理の問題へ応用しいくつかの成果が得られた．

  • 情報理論に基づく学習の一般モデル・アルゴリズムの研究

    2000  

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    　本研究は学習を様々な研究領域について横断的に、情報の視点から考察していく。特に、情報の視点では情報理論と決定理論から学習における情報の流れを整理し、学習の目的や学習対象から学習者にどのように情報が与えれられるかのモデルについて考察する。　学習問題は情報量の観点から簡単に説明がつき、対象から得られた情報から学習目的のために必要な情報を最大限抽出することが最適な学習法と位置づけられる。この最適な学習は情報理論のユニヴァーサル情報源符号化の限界やベイズ決定理論における最悪の事前分布の設定問題と密接な関係にあることも明らかになってきている。　本研究では上記の今までの成果をふまえて、人工知能の機械学習の問題のみならず、さらに様々な領域の学習問題に対して情報理論や決定理論などを基礎とする情報の視点から横断的に考察を行っていくことになり、これまでに以下のような結果を得ている。　各学習問題の目的、学習結果の評価基準、学習対象から与えられる情報の流れのモデル、学習アルゴリズム等を情報の視点で再整理し、その問題個別の特徴、全てに共通の性質などを明確にした。　情報の視点から本質的には同等のアルゴリズムを抽出し、それを一般化することで学習の基本モデルとアルゴリズムを新たに構築した。このアルゴリズムの限界や性質について情報理論や決定理論をはじめ幾つかの視点から考察し、また、それぞれの個別の問題で有効なアルゴリズムについては、学習問題の条件から、そのアルゴリズムの有効性に効いている条件を情報の視点から分類整理し相互の関連を明らかにした。　さらに、各分野の個々の学習問題に対して構築した基本モデルとアルゴリズムの適用を試み、さらにその問題の特殊性が分類整理された学習モデルの条件のどれと類似しているかを検討し、有効なアルゴリズムのそのままの適応やそれを拡張した新たなアルゴリズムの提案を行った。個々の問題において適用あるいは提案したアルゴリズムの性質についても理論面からの考察と、シミュレーションなど実験面からの考察も行った。

  • メディアネットワークにおける高圧縮符号化技術に関する研究

    1998  

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    ネットワーク情報化社会において、情報の圧縮技術は欠く事のできない基盤技術となりつつある。情報圧縮符号化の領域は大別してテキストデータ等の圧縮に利用されている無歪(可逆)圧縮と音声や画像の圧縮に利用されている有歪(非可逆)圧縮の2つがある。 前者では Ziv-Lempel符号を用いた符号が実用化されており、この符号は漸近的に理論的圧縮限界であるエントロピーまで圧縮可能な優れた符号である。しかし、その収束の速さは遅く、最適でないことが知られている。1％でも圧縮率を上げたいという情報化時代のニーズから考えると、新たな符号の提案、実用化が待たれていたが、近年、情報理論の分野でユニヴァーサル無歪圧縮の収束の速さの理論的限界とそれを達成するベイズ符号が提案された。また、木構造を有効に用いたこの符号のアルゴリズムも提案され、理論ばかりでなく実用化についても可能性が開けつつある。研究者たちも理論と符号化アルゴリズム両面でほとんど同時期に同様の成果を発表し、その後もこの研究を発展させ、理論と応用の両面で幾つかの成果を得た。　また、このベイズ的アプローチは統計的推論、モデル選択や学習理論の面への応用も可能で、それらの分野においても新たなアルゴリズム提案や性能の漸近的評価等幾つかの成果を得ることが出来た。

  • マルチメディアにおける高圧縮符号化技術に関する研究

    1997  

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    ネットワーク情報化社会において、情報の圧縮技術は欠く事のできない基盤技術となりつつある。テキストデータ等の圧縮に利用されている無歪(可逆)圧縮では、圧縮限界であるエントロピーへの収束の速さの理論的限界を達成するベイズ符号が近年提案された。また、木構造を有効に用いたこの符号のアルゴリズムも提案され、理論ばかりでなく実用化についても可能性が開けつつある。研究者たちも理論と符号化アルゴリズム両面でほとんど同時期に同様の成果を発表し、その後もこの研究を発展させている。　本研究は無歪みのユニバーサル符号であるベイズ符号の基礎研究が起点となる。ベイズ符号の限界や性質などの情報理論的研究はベイズ決定理論からの理論的解析が中心となる。またベイズ符号の実用化に向けての計算機科学的研究はアルゴリズム論による考察や計算機実験による性能評価が中心となる。この理論、実用両方向からの研究を独立して行うのではなく交互のやりとりにより幾つかの知見が得られた。 理論研究では、より広い情報源のクラスやメモリーが有限の場合の圧縮限界について研究を行なった。実用化アルゴリズムの検討としては、シミュレーションにより、上記の理論式との対応を検討すると共にいくつかの既存のアルゴリズムとの融合も試みた。例えば、ベイズ符号についての理論的共通点が指摘されており、実用化のためのさまざまな工夫が既に行われているZiv-Lempel符号の実用アルゴリズムの一部が、ベイズ符号にも流用可能であれると考えられ、本研究で新たに提案した両者の中間的なアルゴリズムが Ziv-Lempel符号の定数倍の計算量で、FSMX情報源に対してZiv-Lempelより低い圧縮率を達成した。また、ベイズ符号やベイズ最適決定を、モデル選択や知識情報処理などに応用した研究も行い、幾つかの成果が得られている。研究の成果発表：1997/6, IEEE Int. Symp. on IT, Asymptotic property of sufficient statistic codes 1997/6, IEEE Int. Symp. on IT, A study on difference of codelengths between MDL codes and Bayes codes on case different priors are assumed1997/9, 電子情報通信学会論文誌A, Berlekamp-Masseyアルゴリズムを用いたBCH限界を超える復号法の計算量について1997/10 IEEE Int. Symp. on SMC, A learning with membership queries to minimize prediction error1997/10 IEEE Int. Symp. on SMC, Machine learning by a subset of hypotheses1997/10 IEEE Int. Symp. on SMC, A new architecture of signature analyzer for multi-output circuit1998/3, 人工知能学会誌, 矛盾を含む知識の取り扱いについての一考察1997/5, 信学技報／電子情報通信学会, ハッシュ技法によるデータ探索の数学的モデル化,及び探索効率の漸近的評価1997/5, 春季大会予稿集／日本経営工学会, 属性値の類似度を用いた概念学習の効率1997/5, 経営情報学会, 属性のクラスタを用いた概念学習の効率化1997/6, 人工知能学会全国大会(第11回)論文集／人工知能学会, 統計的決定理論によるデータ検索の定式化と最適化1997/7, 信学技報／電子情報通信学会, ベイズ決定理論に基づく統計的モデル選択について1997/7, 信学技報／電子情報通信学会, ベイズ統計学に基づく計算論的学習モデルと学習可能性1997/7, 信学技報／電子情報通信学会, 構造モデル族の学習,予測アルゴリズムに関する一1997/7, 信学技報／電子情報通信学会, トレリス符号を用いた有歪みデータ圧縮の一考察1997/7, 信学技報／電子情報通信学会, 不均一誤り訂正符号の復号法に関する一考察1997/12, 第20回情報理論とその応用シンポジウム予稿集, 階層的確率モデルにおけるタイプについて1997/12, 第20回情報理論とその応用シンポジウム予稿集, 不確実性を含むデータの統合に関する一考1997/12, 第20回情報理論とその応用シンポジウム予稿集, ベイズ符号の視点からのZiv-Lempel78符号の改良に関する一考察1997/12, 第20回情報理論とその応用シンポジウム予稿集, ベイズ符号化法におけるメモリの問題点に関する一考察1997/12, 第20回情報理論とその応用シンポジウム予稿集, 決定を考慮したベクトル量子化法の提案1997/12, 第20回情報理論とその応用シンポジウム予稿集, 木構造型モデル族のモデル選択法に関する一考察1997/12, 第20回情報理論とその応用シンポジウム予稿集, 混合分布の近似とその性能について1997/12, 第20回情報理論とその応用シンポジウム予稿集, 直交表現された仮説の学習に関する一考察1997/12, 第20回情報理論とその応用シンポジウム予稿集, 質問からの学習における予測誤りに関する一考察1997/12, 第20回情報理論とその応用シンポジウム予稿集, BCH限界を超える復号アルゴリズムを用いたChase復号法の計算量低減1998/1, 信学技報／電子情報通信学会, 階層モデル族のモデル選択における選択誤り率について

  • 情報理論に基づく柔らかな情報処理に関する研究

    1995  

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    人間のもつ学習・認識などの機能をマシン上に実現し，あいまいや誤った情報にも適応できる柔らかい情報システム実現のためには従来の理論を基礎とした体系では不十分であり，論理プラスアルファの体系が必要となってきている。 研究者らは柔らかい情報処理の要素である不確実な推論と学習のための基礎理論体系として，第一階言語の解釈空間に確率測度を導入した確率世界論理を数年前より提案し，いくつかの推論を情報の変換としてこの基礎体系上でモデル化し，情報理論の立場から評価基準の明確化や最適な推論アルゴリズムの提案を行っている。 今年度得られた成果としては，矛盾を含んだ知識の管理法と推論法，配列構造を用いた不確実な知識の表現と推論法，質問を許す学習の最適化，収益を最大化を目的とする強化学習アルゴリズムなどが上げられる。 例えば，矛盾を含んだ知識の管理法と推論法では，矛盾が生じるメカニズムを情報理論のモデルにより定式化することにより新たな手法を提案している。質問を許す学習の最適化では，質問回数一定のもとで誤り率最小や誤り率一定のもとで平均質問回数最小の基準の下で最適な学習アルゴリズムを情報理論的上界をうまく使うことによって，提案している。

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