| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2023-12-21 10:55 |
Tokyo | National Institute of Informatics (Primary: On-site, Secondary: Online) |
On the benefits of Partial Stochastic Bayesian Neural Networks Koki Sato, Daniel Andrade (Hiroshima Univ.)  IBISML2023-36 |
Bayesian neural networks (BNNs) can model uncertainty in the prediction results better than ordinary neural networks. Ho... [more] | IBISML2023-36 pp.37-41 |
| NS, RCS (Joint) |
2020-12-17 11:25 |
Online | Online | Improvement on Signal Detection Performance with HMC in Massive MIMO Kazushi Matsumura, Junichiro Hagiwara, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa, Takanori Sato (Hokkaido Univ.) RCS2020-135 |
In massive MIMO, a new technology for wireless transmission, various approaches to reduce the computational complexity a... [more] | RCS2020-135 pp.7-12 |
| RCS | 2020-06-25 14:30 |
Online | Online | A Study on Signal Detection in Massive MIMO Using MCMC Kazushi Matsumura, Junichiro Hagiwara, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa, Takanori Sato (Hokkaido Univ.) RCS2020-38 |
MIMO is a new technology for wireless transmission; as the number of antennas increases, the computational complexity of... [more] | RCS2020-38 pp.91-95 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-17 17:10 |
Okinawa | Okinawa Institute of Science and Technology | MCMC for Value-at-Risk estimation Igor Zavialov, Kazushi Ikeda (NAIST) NC2019-11 |
Value-at-Risk models (VaR) are powerful tools for financial risk management and are widely used by regulating authoritie... [more] | NC2019-11 pp.41-44 |
| R | 2018-05-25 15:30 |
Aichi | Aichi Institute of Technology, Motoyama Campus | Bayesian Interval Estimation of Optimal Software Release Time Based on a Discretized NHPP Model Shinji Inoue (Kansai Univ.), Shigeru Yamada (Tottori Univ.) R2018-4 |
We discuss an approach for obtaining interval estimation of optimal software release time which is derived by a discreti... [more] | R2018-4 pp.19-24 |
| R | 2017-07-28 16:50 |
Hokkaido | Wakkanai Sun Hotel | Software Reliability Assessment Based on a Discretized Model by Bayes' Theory Shinji Inoue (Kansai Univ.), Shigeru Yamada (Tottori Univ.) R2017-23 |
We discuss an interval estimation approach for model parameters and software reliability assessment measures of a discre... [more] | R2017-23 pp.55-60 |
| IT | 2016-12-13 14:50 |
Gifu | Takayama Green Hotel | [Invited Talk]
Recent topics in Markov-chain Monte Carlo method Koji Hukushima (The Univ. of Tokyo) IT2016-43 |
Monte Carlo (MC) methods have been applied to a large class of problems as a numerical tool for sampling from a high-d... [more] |
IT2016-43 pp.9-14 |
| 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 |
| 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 | 2011-11-10 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 |
| 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 |
|
| SIS | 2010-06-10 15:50 |
Hokkaido | Abashiri Public Auditorium | A Study on Efficient Pedestrian Recognition using Markov Chain Monte Carlo Jaehoon Yu (Osaka Univ.), Hiroki Sugano, Ryusuke Miyamoto (NAIST), Takao Onoye (Osaka Univ.) SIS2010-12 |
For object detection including pedestrian detection, sliding window approach is widely used, in which classification usi... [more] | SIS2010-12 pp.65-70 |
| 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 |
[Return to Top Page]