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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IT | 2019-07-26 10:30 |
Tokyo | NATULUCK-Iidabashi-Higashiguchi Ekimaeten | Unbiased Estimation Equation for f-Separable Bregman Distortion Measures and the Properties of Its Estimators Masahiro Kobayashi, Kazuho Watanabe (Toyohashi Tech.)  IT2019-22 |
In this study, we discuss unbiased estimation equations in a class of objective function using the monotonically increas... [more] | IT2019-22 pp.37-42 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Generalized Dirichlet-Process-Means with f-Mean and Analysis of Influence Function Masahiro Kobayashi, Kazuho Watanabe (Toyohashi Tech.) IBISML2018-50 |
DP-means clustering was obtained as an extension of $K$-means clustering. While it is implemented with a simple and effi... [more] | IBISML2018-50 pp.45-52 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Bregman monotone operator splitting and its application example Kenta Niwa (NTT), W. Bastiaan Kleijn (VUW) IBISML2018-80 |
Monotone operator splitting is a powerful paradigm that facilitates parallel processing for optimization problems where ... [more] | IBISML2018-80 pp.271-278 |
| IT | 2016-12-13 15:50 |
Gifu | Takayama Green Hotel | [Invited Talk]
Bregman Divergence and its Applications Takafumi Kanamori (Nagoya Univ.) IT2016-44 |
In statistical inference and machine learning, Bregman divergences are often used. This paper shows applications of Breg... [more] | IT2016-44 pp.15-20 |
| PRMU | 2013-12-12 15:50 |
Mie | Enzyme Active Site Prediction Using Bregman Divergence Regularized Machine Raissa Relator, Tsuyoshi Kato (Gunma Univ.), Nozomi Nagano (AIST) PRMU2013-78 |
- [more] | PRMU2013-78 pp.61-66 |
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| IBISML | 2012-06-19 11:00 |
Kyoto | Campus plaza Kyoto | Online Prediction under Submodular Constraints Daiki Suehiro, Kohei Hatano, Shuji Kijima, Eiji Takimoto (Kyushu Univ.), Kiyohito Nagano (Tokyo Univ.) IBISML2012-3 |
[more] | IBISML2012-3 pp.15-22 |
| NC | 2011-07-25 13:45 |
Hyogo | Graduate School of Engineering, Kobe University | General Framework for Local Variational Approximation of Bayesian Learning Using Bregman Divergence Kazuho Watanabe (NAIST), Masato Okada (Univ. of Tokyo), Kazushi Ikeda (NAIST) NC2011-25 |
The local variational method is a technique to approximate an intractable posterior distribution in Bayesian learning. T... [more] | NC2011-25 pp.25-30 |
| IBISML | 2010-11-04 15:00 |
Tokyo | IIS, Univ. of Tokyo | [Poster Presentation]
A Unified Framework of Density Ratio Estimation under Bregman Divergence Masashi Sugiyama (Tokyo Inst. of Tech.), Taiji Suzuki (Univ. of Tokyo), Takafumi Kanamori (Nagoya Univ.) IBISML2010-64 |
Estimation of the ratio of probability densities has attracted a great deal of attention since it can be used for addre... [more] |
IBISML2010-64 pp.33-44 |
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