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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
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 |
2014-11-17 17:00 |
Aichi |
Nagoya Univ. |
[Poster Presentation]
Theoretical Analysis of Empirical MAP and Empirical Partially Bayes Shinichi Nakajima (TU Berlin), Masashi Sugiyama (Univ. of Tokyo) IBISML2014-38 |
Variational Bayesian (VB) learning is known to be a
promising
approximation to Bayesian learning
with computational... [more] |
IBISML2014-38 pp.25-32 |
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 |
NC, MBE (Joint) |
2010-03-10 14:35 |
Tokyo |
Tamagawa University |
Information Divergences in Local Variational Approximation of Bayesian Posterior Distribution Kazuho Watanabe (NAIST), Masato Okada (Univ. of Tokyo), Kazushi Ikeda (NAIST) NC2009-138 |
Local variational method is a technique to approximate intractable posterior distributions in Bayesian learning.
In thi... [more] |
NC2009-138 pp.297-302 |
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