| Presentation | 2011-07-25 General Framework for Local Variational Approximation of Bayesian Learning Using Bregman Divergence Kazuho WATANABE, Masato OKADA, Kazushi IKEDA, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The local variational method is a technique to approximate an intractable posterior distribution in Bayesian learning. This article formulates a general framework for local variational approximation using the Bregman divergence. Based on a geometrical argument in the space of approximating posteriors, we propose an efficient method to evaluate an upper bound of the marginal likelihood. We demonstrate its application to the kernelized logistic regression model and numerically investigate the accuracy of approximation. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Bayesian Learning / Local Variational Approximation / Kullback Information / Bregman Divergence / Kernelized Logistic Regression |
| Paper # | NC2011-25 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2011/7/18(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | General Framework for Local Variational Approximation of Bayesian Learning Using Bregman Divergence |
| Sub Title (in English) | |
| Keyword(1) | Bayesian Learning |
| Keyword(2) | Local Variational Approximation |
| Keyword(3) | Kullback Information |
| Keyword(4) | Bregman Divergence |
| Keyword(5) | Kernelized Logistic Regression |
| 1st Author's Name | Kazuho WATANABE |
| 1st Author's Affiliation | Graduate School of Information Science, Nara Institute of Science and Technology() |
| 2nd Author's Name | Masato OKADA |
| 2nd Author's Affiliation | Department of Complexity Science and Engineering, The University of Tokyo |
| 3rd Author's Name | Kazushi IKEDA |
| 3rd Author's Affiliation | Graduate School of Information Science, Nara Institute of Science and Technology |
| Date | 2011-07-25 |
| Paper # | NC2011-25 |
| Volume (vol) | vol.111 |
| Number (no) | 157 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |