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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2023-06-30 13:55 |
Okinawa | OIST Conference Center (Primary: On-site, Secondary: Online) |
Exploring Regioselective Catalysts with Hierarchical Bandits Hongyuan Guo, Koji Tabata, Yoshihiro Matsumura, Tamiki Komatsuzaki (Hokkaido Univ.)  NC2023-17 IBISML2023-17 |
In selective chemical reactions, controlling the reaction site is crucial in synthetic organic chemistry. This study foc... [more] | NC2023-17 IBISML2023-17 pp.106-112 |
| CCS, NLP | 2022-06-10 16:45 |
Osaka | (Primary: On-site, Secondary: Online) |
Motion artifact reduction in EEG recordings using the multivariate temporal response function of acceleration signals with hyperparameter estimation Hiroaki Umehara, Yusuke Yokota (NICT), Masato Okada (UTokyo/NICT), Yasuishi Naruse (NICT) NLP2022-24 CCS2022-24 |
The recent advances of wearable electroencephalography (EEG) systems with dry electrodes provide the realization of brai... [more] | NLP2022-24 CCS2022-24 pp.123-128 |
| NC, MBE (Joint) |
2020-03-05 13:00 |
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 pp.107-112 |
| IBISML | 2020-01-09 13:25 |
Tokyo | ISM | Real Log Canonical Threshold of Three Layered Neural Network with Swish Activation Function Raiki Tanaka, Sumio Watanabe (Tokyo Tech) IBISML2019-19 |
In neural network learning, it is known that selection of activation function effects generalization performance. Althou... [more] | IBISML2019-19 pp.9-15 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Inference for Logitistic Regression Mixture Model with Local Variational Approximation and Study for Variational Free Energy Fumito Nakamura, Ryosuke Konishi (Generic Solution), Yasushi Kiyoki (Keio) IBISML2018-48 |
A logistic regression mixture model (LRMM) is a mixed model of the Logistic regression model, and it is widely used in t... [more] | IBISML2018-48 pp.29-36 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Variational Approximation Accuracy in Non-negative Matrix Factorization Naoki Hayashi (MSI) IBISML2018-51 |
The asymptotic behavior of the variational free energy of the non-negative matrix factorization (NMF) has been elucidate... [more] | IBISML2018-51 pp.53-60 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Normal mode selection of coherent phonons by Bayesian LARS-OLS Itsushi Sakata, Yoshihiro Nagano (UTokyo), Yasushiko Igarashi (JST), Shin Murata (UTokyo), Kohji Mizoguchi (Osaka Prefecture Univ.), Ichiro Akai (Kumamoto Univ.), Masato Okada (UTokyo) IBISML2018-78 |
Coherent phonon (CP) signals contain normal modes representing the material property and experimental artifacts. It is p... [more] | IBISML2018-78 pp.255-262 |
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | Gaussian Markov random field model without periodic boundary conditions Shun Katakami, Hirotaka Sakamoto, Shin Murata, Masato Okada (UTokyo) IBISML2016-83 |
In this study, we discuss Gaussian Markov random field model without periodic boundary conditions. First, we formulate a... [more] | IBISML2016-83 pp.267-274 |
| NC | 2011-07-26 11:00 |
Hyogo | Graduate School of Engineering, Kobe University | Image Segmentation and Restoration using Region-Based Hidden Variables and Belief Propagation Ryota Hasegawa (Kansai Univ.), Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.) NC2011-35 |
We derive a deterministic algorithm that restores and segments an image using belief propagation and a variational Bayes... [more] | NC2011-35 pp.81-86 |
| IBISML | 2010-11-04 15:00 |
Tokyo | IIS, Univ. of Tokyo | [Poster Presentation]
Image Segmentation by Region-Based Latent Variables and Belief Propagation Ryota Hasegawa, Seiji Miyoshi (Kansai Univ.), Masato Okada (Univ. of Tokyo) IBISML2010-71 |
To represent edges in image processing based on Bayesian inference, it is very effective to introduce latent variables. ... [more] | IBISML2010-71 pp.91-97 |
| 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 |
| NC | 2008-10-23 10:15 |
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 pp.19-24 |
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