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Committee Date Time Place Paper Title / Authors Abstract Paper #
Miyagi Tohoku Univ.
(Primary: On-site, Secondary: Online)
An approximation algorithm for computing integrated information based on Gaussian process regression
Tadaaki Hosaka (TUS) NC2022-40
The framework of Integrated Information Theory, which aims to mathematically deal with consciousness, consists of multip... [more] NC2022-40
IT 2022-07-22
Okayama Okayama University of Science
(Primary: On-site, Secondary: Online)
An Efficient Algorithm for Optimal Decision on Piecewise Linear Regression Model by Bayes Decision Theory
Noboru Namegaya, Koshi Shimada, Toshiyasu Matsushima (Waseda Univ.) IT2022-25
In this study, we propose a Beyes-optimal prediction method on a piecewise linear regression model by Bayes decision the... [more] IT2022-25
IBISML 2021-03-03
Online Online Markov Decision Processes for Simultaneous Control of Multiple Objects with Different State Transition Probabilities in Each Cluster
Yuto Motomura, Akira Kamatsuka, Koki Kazama, Toshiyasu Matsushima (Waseda Univ.) IBISML2020-49
In this study, we propose an extended MDP model, which is a Markov decision process model with multiple control objects ... [more] IBISML2020-49
IT, EMM 2020-05-28
Online Online Bayes Optimal Detecting Relevant Changes for i.p.i.d. Sources
Kairi Suzuki, Akira Kamatsuka, Toshiyasu Matsushima (Waseda Univ.) IT2020-3 EMM2020-3
The problems of detecting change points are studied in various fields.
There are various types of change-point detectio... [more]
IT2020-3 EMM2020-3
ISEC, IT, WBS 2020-03-10
Hyogo University of Hyogo
(Cancelled but technical report was issued)
A Statistical Decision-Theoretic Approach for Measuring Privacy Risk in Information Disclosure Problem
Alisa Miyashita, Akira Kamatsuka (Waseda Univ.), Takahiro Yoshida (Yokohama College of Commerce), Toshiyasu Matsushima (Waseda Univ.) IT2019-104 ISEC2019-100 WBS2019-53
In this paper, we deal with the problem of database statistics publishing with privacy and utility guarantees. While var... [more] IT2019-104 ISEC2019-100 WBS2019-53
Tokyo University of Electro Communications
(Cancelled but technical report was issued)
Bayesian learning curve for the case when the optimal distribution is not unique
Shuya Nagayasu, Sumio Watanabe (Tokyo Tech) NC2019-94
Bayesian inference is a widely used statistical method. Asymptotic behaviors of generalization loss and free energy in B... [more] NC2019-94
ISEC, SITE, ICSS, EMM, HWS, BioX, IPSJ-CSEC, IPSJ-SPT [detail] 2019-07-24
Kochi Kochi University of Technology Stochastic Existence Connecting Logos that are not necessarily completely divided and Language Games -- Limitations of Security Models and the Possibility of Artificial Intelligence --
Tetsuya Morizumi (KU) ISEC2019-49 SITE2019-43 BioX2019-41 HWS2019-44 ICSS2019-47 EMM2019-52
In this paper we describe that AI architecture including input data in artificial intelligence system for Bayesian estim... [more] ISEC2019-49 SITE2019-43 BioX2019-41 HWS2019-44 ICSS2019-47 EMM2019-52
EA 2018-12-14
Fukuoka kyushu Univ. Bayesian Filter for Sound Environment by Considering Additive Property of Energy Variable and Fuzzy Observation in Decibel Scale -- Introduction of Fuzzy Moments --
Akira Ikuta, Hisako Orimoto (Prefectural Univ. Hiroshima) EA2018-89
In the measurement and evaluation of actual random signal in a sound environment, the observed data often contain the fu... [more] EA2018-89
IBISML 2018-11-05
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Active learning for identifying local minimum points based on the derivative of Gaussian process
Yu Inatsu (RIKEN), Daisuke Sugita (NITech), Kazuaki Toyoura (Kyoto Univ.), Ichiro Takeuchi (NITech/RIKEN/NIMS) IBISML2018-94
In many fields such as materials science, knowing local minimum points of unknown functions is important for understand... [more] IBISML2018-94
IBISML 2018-11-05
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] A Note on the Estimation Method of Causality Effects based on Statistical Decision Theory
Shunsuke Horii, Tota Suko (Waseda Univ.) IBISML2018-97
In this paper, we deal with the problem of estimating the intervention effect in statistical causal analysis using struc... [more] IBISML2018-97
NS 2018-10-19
Kyoto Kyoto Kyoiku Bunka Center [Invited Lecture] Study of Internet Traffic Classification Based on Naive Bayesian Method
Yuanzhi Shao (UEC), Ved P. Kafle (NICT) NS2018-127
The traditional port- and payload-based traffic detection and classification technique may not meet the security and QoS... [more] NS2018-127
MSS 2017-03-16
Shimane Shimane Univ. Finding the Candidates of Attributes in Mail Words Filtered by Bayesian Method
Nozomi Fujii, Manabu Sugii, Hiroshi Matsuno (Yamacguchi Univ.) MSS2016-89
The interest of a research about mail-filtering system is in a method based on Bayesian theory.The existing systems for ... [more] MSS2016-89
IT, ISEC, WBS 2016-03-10
Tokyo The University of Electro-Communications Bayesian Estimation of the Virus Source of an Infection in a Network Using Any Prior Distribution
Ryousuke Kido, Tetsunao Matsuta, Ryutaroh Matsumoto, Tomohiko Uyematsu (Tokyo Tech.) IT2015-104 ISEC2015-63 WBS2015-87
We model a phenomenon that a computer virus is spreading in a network as infection of the virus in a graph constructed o... [more] IT2015-104 ISEC2015-63 WBS2015-87
Miyagi Tohoku University A Bayesian Network Model of theory-of-mind
Naoya Nishio, Nobuhiko Asakura, Toshio Inui (Kyoro Univ.) NC2014-39
Theory of mind (ToM) is a knowledge and cognitive framework for understanding the minds of others and predicting their a... [more] NC2014-39
PRMU, IBISML, IPSJ-CVIM [detail] 2013-09-02
Tottori   [Invited Talk] Topics on the Cost in Machine Learning
Shotaro Akaho (AIST) PRMU2013-40 IBISML2013-20
Most machine learning algorithms minimize some cost functions, therefore
the cost is a general target of research.
... [more]
PRMU2013-40 IBISML2013-20
NC 2012-07-31
Shiga Ritsumeikan Univ. College of Information Science and Engineering A Biological Implementation of Bayesian Estimation Algorithm in a Neural Network Architecture Based on Discrete Choice Theory
Daiki Futagi, Ryota Kobayashi, Katsunori Kitano (Ritsumeikan Univ) NC2012-28
Bayesian estimation theory has been expected to explain how brain deals with uncertainty such as feature extraction agai... [more] NC2012-28
IBISML 2011-11-10
Nara Nara Womens Univ. Sequential Network Change Detection with Its Applications to Advertisement Impact Relation Analysis
Yu Hayashi, Kenji Yamanishi (Univ. of Tokyo.) IBISML2011-71
This paper addresses the issue of network change detection from non-stationary time series data. We employ as a represen... [more] IBISML2011-71
IBISML 2011-06-20
Tokyo Takeda Hall Network Change Detection with Its Applications to Advertisement Impact Relation Analysis
Yu Hayashi, Kenji Yamanishi (Univ. of Tokyo.) IBISML2011-9
This paper addresses the issue of network change detection with its applications to advertisement impact relation analys... [more] IBISML2011-9
- 2010-12-17
Miyazaki Miyazaki Seagai resort Analysis of Psychological Stress Factors with Spontaneous Facial Expressions using Bayesian Networks
Hiroaki Otsu, Kazuhito Sato, Hirokazu Madokoro (Akita Prefectural Univ.), Sakura Kadowaki (SmartDesign)
This paper presents a method to create an individual model to describe relations between facial expressions and stress p... [more]
NC 2008-10-23
Miyagi Tohoku Univ. Statistical Mechanical Approach for Computational Neuroscience -- With the use of the Primary Visual Area Model --
Ken Takiyama (Tokyo Univ.), Yasushi Naruse (NICT), Masato Okada (Tokyo Univ./RIKEN BSI) NC2008-39
In this study, we propose a multi-hypercolumn model consisting of $K$ hypercolumns. Adjacent hypercolumns have inter-hyp... [more] NC2008-39
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