| Presentation | 2005/3/23 The Accuracy of Mean Field Approximation as an Approach of the True Bayesian Learning Nobuhiro NAKANO, Sumio WATANABE, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Mean field approximation is proposed as an approach of the Bayesian learning in order to overcome intractability of computing the Bayesian posterior distributions. However, it remains unknown how precise mean field approximation in singular learning machines is. In this paper, we consider a case when a three-layer perceptron that includes the true distributionis is trained to estimate the true one, and derive its asymptotic stochastic complexity that enables us to discuss the accuracy of mean field approximation as an approach of the true Bayesian learning. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Algebraic Geometry / Stochastic Complexity / Learning Machines with Singularities / Mean Field Approximation |
| Paper # | NC2004-212 |
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| Committee | NC |
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| Conference Date | 2005/3/23(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 | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | The Accuracy of Mean Field Approximation as an Approach of the True Bayesian Learning |
| Sub Title (in English) | |
| Keyword(1) | Algebraic Geometry |
| Keyword(2) | Stochastic Complexity |
| Keyword(3) | Learning Machines with Singularities |
| Keyword(4) | Mean Field Approximation |
| 1st Author's Name | Nobuhiro NAKANO |
| 1st Author's Affiliation | Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology() |
| 2nd Author's Name | Sumio WATANABE |
| 2nd Author's Affiliation | P&I Lab., Tokyo Institute of Technology |
| Date | 2005/3/23 |
| Paper # | NC2004-212 |
| Volume (vol) | vol.104 |
| Number (no) | 760 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |