| Presentation | 2004/10/12 Stochastic Complexities in Learning of Normal Mixture Models by Variational Bayes Approach Kazuho WATANABE, Sumio WATANABE, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The Variational Bayes approach, proposed as an approximation of the Baysian learning, has provided computational tractability and good generalization performance in many applications. In spite of these advantages, the properties and capabilities of the Variational Bayes learning itself have not been clarified yet. It is still unknown how good approximation the Variational Bayes approach can achieve. In this paper, we discuss the Variational Bayes learning of normal mixture models and derive the lower bounds of the stochastic complexities that show us the accuracy of Variational Bayes learning as an approximation. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Normal Mixture Model / Variational Bayes Learning / Stochastic Complexity / Singular Statistical Model |
| Paper # | NC2004-78 |
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| Committee | NC |
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| Conference Date | 2004/10/12(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| 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) | Stochastic Complexities in Learning of Normal Mixture Models by Variational Bayes Approach |
| Sub Title (in English) | |
| Keyword(1) | Normal Mixture Model |
| Keyword(2) | Variational Bayes Learning |
| Keyword(3) | Stochastic Complexity |
| Keyword(4) | Singular Statistical Model |
| 1st Author's Name | Kazuho WATANABE |
| 1st Author's Affiliation | Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology() |
| 2nd Author's Name | Sumio WATANABE |
| 2nd Author's Affiliation | P&I Lab, Tokyo Institute of Technology |
| Date | 2004/10/12 |
| Paper # | NC2004-78 |
| Volume (vol) | vol.104 |
| Number (no) | 349 |
| Page | pp.pp.- |
| #Pages | 6 |
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