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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2014-03-06 13:50 |
Nara | Nara Women's University | Finding scale-free networks of Gaussian graphical models by sampling Shota Shikita, Osamu Maruyama (Kyushu Univ.)  IBISML2013-69 |
The problem of learning the structure of a Gaussian graphical model is to infer the graph representing the relationship ... [more] | IBISML2013-69 pp.15-22 |
| DC | 2012-12-14 13:45 |
Fukui | Aossa (Fukui) | Mobile device prediction for location-based cloud service Haibo Yan, Masato Kitakami (Chiba Univ.) DC2012-73 |
Mobility prediction is one of the most essential issues which need to be explored for management in a location-based clo... [more] | DC2012-73 pp.1-4 |
| IN, IA (Joint) |
2012-12-13 18:20 |
Hiroshima | Hiroshima City Univ. | [Invited Talk]
Analysis of SNS Network using Precision Family-network Approximation Based on Multi-modal Nonlinear Markov-Transition Takeshi Ozeki (Sophia Univ.) IN2012-126 IA2012-64 |
Our motivation of communication network study is to find an abstractive network theory or methodology applicable to vari... [more] | IN2012-126 IA2012-64 pp.25-32(IN), pp.31-38(IA) |
| IBISML | 2012-11-08 15:00 |
Tokyo | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. | MCMC Strategy for Protein Complex Prediction Using Cluster Size Frequency Daisuke Tatsuke, Osamu Maruyama (Kyushu Univ.) IBISML2012-91 |
In this paper we propose a Markov chain Monte Carlo sampling method for predicting protein complexes from protein-prote... [more] |
IBISML2012-91 pp.409-416 |
| VLD, DC, IPSJ-SLDM, CPSY, RECONF, ICD, CPM (Joint) [detail] |
2011-11-28 16:30 |
Miyazaki | NewWelCity Miyazaki | A study on parameter estimation for modeling of random-telegraph noise Hiromitsu Awano, Hirofumi Shimizu, Hiroshi Tsutsui, Hiroyuki Ochi, Takashi Sato (Kyoto Univ.) VLD2011-66 DC2011-42 |
Random Telegraph Noise (RTN) is a physical phenomenon that is considered to determine reliability and performance of cir... [more] | VLD2011-66 DC2011-42 pp.85-90 |
| IBISML | 2011-11-09 15:45 |
Nara | Nara Womens Univ. | Adaptive Markov Chain Monte Carlo for Auxiliary Variable Method and Its Application to Exchange Monte Carlo Method Takamitsu Araki, Takashi Takenouchi, Kazushi Ikeda (NAIST) IBISML2011-47 |
For sampling from a complicated distribution, Auxiliary Variable Method, which contain Exchange Monte Carlo Method and C... [more] | IBISML2011-47 pp.33-38 |
| IBISML | 2011-11-10 15:45 |
Nara | Nara Womens Univ. | Image segmentation and restoration by variational Bayesian method and MCMC Kenta Kayano (Kansai Univ.), Kenji Nagata, Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.) IBISML2011-68 |
In this paper, we derive a deterministic algorithm that restores and segments an image by using variational Bayesian met... [more] | IBISML2011-68 pp.175-180 |
| MI | 2011-07-13 10:30 |
Hokkaido | Hokkaido University | Robust Non-rigid surface registration with Confidence Self-Evaluation based on L1-Norm Regularization Yoshihide Sawada, Takamichi Matsuno, Hidekata Hontani (NIT) MI2011-42 |
In this article, we propose a non-rigid surface registration method, which can not only estimate the con fidence of the ... [more] | MI2011-42 pp.49-54 |
| NC, MBE (Joint) |
2011-03-08 13:45 |
Tokyo | Tamagawa University | Comparison between the Parameter and the Hidden Variable Space for Calculation of the Marginal Likelihood Takushi Miki, Keisuke Yamazaki, Sumio Watanabe (Tokyo Tech) NC2010-176 |
The marginal likelihood has important information for model selection and optimization of a prior distribution.In practi... [more] | NC2010-176 pp.289-294 |
| ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] | 2011-02-21 16:25 |
Hokkaido | Hokkaido University | A note on accurate scene segmentation based on the MCMC method using object matching Yan Song, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) ITS2010-46 IE2010-121 |
This paper proposes an accurate scene segmentation method based on the Markov Chain Monte Carlo (MCMC) algorithm using o... [more] | ITS2010-46 IE2010-121 pp.131-135 |
| MI | 2011-01-20 10:45 |
Okinawa | Naha-Bunka-Tembusu | Comparison of the Registration Performance between MCMC-based method and Belief Propagation-based one Yoshihide Sawada, Wataru Watanabe, Hidekata Hontani (NIT) MI2010-90 |
Both Markov chain Monte Carlo (MCMC) and belief propagation (BP) are widely used for inferring posterior distributions o... [more] | MI2010-90 pp.51-56 |
| IT | 2010-11-30 15:20 |
Nagano | [Invited Talk]
Particle Filter and MCMC for Communication Science Kazuhiro Otsuka (NTT, NTT Comm Sci Labs) IT2010-52 |
In recent years, automatic analysis of human conversation scenes has been acknowledged as an emerging research field. Au... [more] | IT2010-52 pp.9-18 |
|
| IBISML, PRMU, IPSJ-CVIM [detail] | 2010-09-06 09:30 |
Fukuoka | Fukuoka Univ. | Proposal of MCMC methods on hidden variables of a nomral mixture and its application to Bayes marginal Likelihood Takushi Miki, Sumio Watanabe (Tokyo Tech) PRMU2010-75 IBISML2010-47 |
The Bayes marginal likelihood has important information for model selection, optimization for hyperparameter.However, ... [more] |
PRMU2010-75 IBISML2010-47 pp.143-148 |
| IBISML | 2010-06-15 13:30 |
Tokyo | Takeda Hall, Univ. Tokyo | [Invited Talk]
Recent Developments in Markov-chain Monte Carlo Method Koji Hukushima (Univ. of Tokyo.) IBISML2010-17 |
(Advance abstract in Japanese is available) [more] | IBISML2010-17 pp.113-118 |
| PRMU, HIP | 2010-03-16 12:20 |
Kagoshima | Kagoshima Univ. | Improvement of Accuracy in Bayesian Hidden Markov Model Approach for Sports Event Detection Tomohiro Yazaki (Waseda Univ.), Toshie Misu (NHK), Yohei Nakada, Shigeru Motoi, Go Kobayashi, Takashi Matsumoto (Waseda Univ.), Nobuyuki Yagi (NHK) PRMU2009-301 HIP2009-186 |
The problem of detecting the occurrence of target events in a given data sequence can be found in many fields , such as ... [more] | PRMU2009-301 HIP2009-186 pp.401-406 |
| PRMU, IE, MI | 2009-05-28 16:15 |
Gifu | Gifu Univ. | Real-time estimation of human visual attention with MCMC-based particle filter Kouji Miyazato (NTT/Okinawa National College of Tech), Akisato Kimura (NTT), Shigeru Takagi (Okinawa National College of Tech), Junji Yamato (NTT) IE2009-25 PRMU2009-16 MI2009-16 |
This report proposes a new method for achieving a precise estimation of human visual attention with considerably less ex... [more] | IE2009-25 PRMU2009-16 MI2009-16 pp.83-88 |
| NC, MBE (Joint) |
2009-03-11 16:10 |
Tokyo | Tamagawa Univ. | Numerical Calculation of Stochastic Complexties through Optimization of Gaussian Mixture centered on MCMC Samples Takayuki Higo, Kenji Nagata, Sumio Watanabe (Tokyo Inst. of Tech.) NC2008-112 |
Stochastic complexity is a criterion for model selection and determination of hyper parameters in Bayesian learning．If s... [more] | NC2008-112 pp.51-56 |
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