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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | Infinite graphs with finite diameters Chihiro Watanabe, Masahiro Nakano, Xiaomeng Wu, Takahito Kawanishi, Kaoru Hiramatsu, Kunio Kashino (NTT)  IBISML2016-77 |
Recently, new stochastic processes have been proposed for analyzing structured data with combinatorial constraints. Part... [more] | IBISML2016-77 pp.221-228 |
| AI | 2014-11-29 13:50 |
Fukuoka | The Marketing Knowledge Network Scheme
-- A Platform to Aggregate Consumer Behavior Models Which Shares the Common Design of Human Mind -- Yoshihide Nishio, Asami Orita, Yinjun Hu, Saori Tsuda, Mathieu Bertin, Kouhei Yamada (Synergy Marketing) AI2014-29 |
We develop a platform called The Marketing Knowledge Network where we collect consumer behavior models built from variou... [more] | AI2014-29 pp.21-25 |
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| ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] | 2014-02-17 10:05 |
Hokkaido | Hokkaido Univ. | A note on estimating deformation based on Bayesian networks using images from bridge inspection Katsuki Kobayashi, Sho Takahashi, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a method for estimating deformation of bridges based on Bayesian networks. There exist strong relati... [more] | |
| IBISML | 2013-11-12 15:45 |
Tokyo | Tokyo Institute of Technology, Kuramae-Kaikan | [Poster Presentation]
Performance Comparisons between Dependency Networks and Bayesian Networks Kazuya Takabatake, Shotaro Akaho (AIST) IBISML2013-41 |
Dependency networks are graphical models in which tasks of learning are done by totally local and simple algorithms of i... [more] | IBISML2013-41 pp.39-44 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2013-09-02 10:30 |
Tottori | Study of Recognizing Spontaneous Facial Expressions of a Person who Watches Web News Based on ASM and Bayesian Network Chao Xu, Jun Ohya (Waseda Univ.) PRMU2013-34 IBISML2013-14 |
To achieve a comment system that can automatically estimate emotions of a person who watches web news, this paper propos... [more] | PRMU2013-34 IBISML2013-14 pp.7-12 |
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| NC | 2012-07-31 11:35 |
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 pp.77-82 |
| MBE, NC (Joint) |
2012-03-14 16:50 |
Tokyo | Tamagawa University | Bayesian Network Associative Memories Hiroaki Hasegawa, Masafumi Hagiwara (Keio Univ.) NC2011-146 |
In this paper, we propose Bayesian Network Associative Memories (BNAMs) for modeling associative memories with Bayesian ... [more] | NC2011-146 pp.147-152 |
| ET | 2012-03-10 13:50 |
Kagawa | Motion Classification Method using Probabilistic Graphical Model and Its Application to Working Posture Analysis Masaru Okamoto, Yuko Akai, Yukihiro Matsubara (Hiroshima City Univ.) ET2011-120 |
In this paper, novel probabilistic motion classification method using position data of body measured from various camera... [more] | ET2011-120 pp.113-118 |
|
| NS, IN (Joint) |
2012-03-09 15:00 |
Miyazaki | Miyazaki Seagia | Evaluation of Information Recommendation Modeling Method on Bayesian Networks for Privacy Preservation Michiomi Itoh, Hiroki Matsuzaki, Toshihiro Nishizono (Nihon Univ) NS2011-273 |
This paper proposes a method to privacy-preserving construct content-based recommendation models based on Bayesian netwo... [more] | NS2011-273 pp.535-540 |
| NC | 2012-01-27 09:55 |
Hokkaido | Future University Hakodate | A Study on Approximate Probabilistic Reasoning Algorithm for assuring and correcting accuracy results on Bayesian Networks Shuhei Wakasaki, Daisuke Kitakoshi, Masato Suzuki (TNCT) NC2011-110 |
In this paper, we propose an approximate probabilistic reasoning algorithm using the connecting structures of Bayesian n... [more] | NC2011-110 pp.77-82 |
| NC, MBE (Joint) |
2011-03-07 17:15 |
Tokyo | Tamagawa University | Improvement of infant's action recognition accuracy by Bayesian estimation method introducing Bayesian Network
-- Experimental evaluation with supersonic sensor and camera images -- Shozo Ishikawa (UEC), Yoichi Motomura, Yoshifumi Nishida (AIST), Hayaru Shouno (UEC) NC2010-150 |
The purpose of this study is to prevent accident in infants. Therefore, we consider analysis the action of the behavior... [more] |
NC2010-150 pp.137-142 |
| IN, NS (Joint) |
2011-03-03 10:00 |
Okinawa | Okinawa Convention Center | A Study on Reinforcement Learning for Improving Fairness in Lightpath Networks Shu Kobuchi, Takuji Tachibana (NAIST), Sugang Xu (NICT) NS2010-167 |
In lightpath networks, lightpaths whose number of hops is large are not established easily than those whose number of ho... [more] | NS2010-167 pp.25-28 |
| IN, NS (Joint) |
2011-03-04 08:30 |
Okinawa | Okinawa Convention Center | Evaluation of Privacy Preservation Recommendation Based on Bayesian Networks Shogo Hachiya, Toshihiro Nishizono (Nihon Univ.) NS2010-242 |
This paper proposes a method for constructing privacy-preserving recommendation models for content-based filtering. Afte... [more] | NS2010-242 pp.439-444 |
| HCGSYMPO (2nd) |
2010-12-15 - 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] | |
| LOIS, IPSJ-DC (Joint) |
2010-07-23 10:15 |
Iwate | Iwate Prefectural Univ. | A location predicton method using dynamic Bayesian networks with ambiguous calendar data and GPS data Masaaki Nishino, Yukihiro Nakamura, Takashi Yagi, Shinyo Muto, Masanobu Abe (NTT Corp.) LOIS2010-15 |
We propose a method for making prediction of future positions of a user by using two different types of logged data R... [more] | LOIS2010-15 pp.29-34 |
| USN, IPSJ-UBI | 2010-07-16 09:50 |
Ibaraki | Tsukuba Univ. | The Design of a Relational Data Stream Processing Engine with Probabilistic Reasoning Hideyuki Kawashima, Hiroyuki Kitagawa, Ryo Sato (Univ. of Tsukuba) USN2010-18 |
The purpose of this paper is to appropriately incorporate Bayesian networks into a relational stream processing system ... [more] |
USN2010-18 pp.109-114 |
| NC, MBE (Joint) |
2010-03-09 16:25 |
Tokyo | Tamagawa University | Probabilistic Interpretation of Border-ownership Signals in Early Visual Cortex Haruo Hosoya (Univ. of Tokyo.) NC2009-100 |
Several recent model studies of visual cortex have used Bayesian networks and their belief propagation algorithms, an... [more] |
NC2009-100 pp.71-76 |
| NS, IN (Joint) |
2010-03-05 14:30 |
Miyazaki | Miyazaki Phoenix Seagaia Resort (Miyazaki) | Information Recommendation Modeling Method for Privacy Preservation Shogo Hachiya, Toshihiro Nishizono (Nihon Univ.) NS2009-254 |
A privacy concealing method is proposed for making recommendation models in information recommendation services based on... [more] | NS2009-254 pp.517-522 |
| PRMU, SP, MVE, CQ | 2010-01-22 09:20 |
Kyoto | Kyoto Univ. | Estimation of Driving Behaviors at Intersections Hideomi Amata, Chiyomi Miyajima, Takanori Nishino, Norihide Kitaoka, Kazuya Takeda (Nagoya Univ.) CQ2009-87 PRMU2009-186 SP2009-127 MVE2009-109 |
In this paper, we investigated the differences in driving behaviors at unsignalized intersections between expert and non... [more] | CQ2009-87 PRMU2009-186 SP2009-127 MVE2009-109 pp.213-218 |
| NLP | 2009-12-21 13:50 |
Iwate | A Searching Method of Plural Dynamic Bayesian Networks Structures Using an Evolutionary Algorithm Kousuke Shibata, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) NLP2009-132 |
In this paper, the author presents an Immune Algorithm(IA) for learning the network structure of DBNs. In the convention... [more] | NLP2009-132 pp.33-36 |
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