| Presentation | 1998/11/17 Learning Theory for Statistical models with singular points based on algebraic analysis Sumio Watanabe, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Mathematical foundation for nonlinear and irregular statistical models such as multi-layer neural networks and gauussian mixutures have not been sufficiently established, because the set of true parameters of them is an algeraic variety with singularities. This paper proposes a method to clarify the general learning curves by measuring the depth of the singular points based on the theory for Sato's b-functions. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Irregular statistical model / Algebraic Analysis / Algebraic variety / Sato's b function |
| Paper # | NC98-64 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1998/11/17(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 | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Learning Theory for Statistical models with singular points based on algebraic analysis |
| Sub Title (in English) | |
| Keyword(1) | Irregular statistical model |
| Keyword(2) | Algebraic Analysis |
| Keyword(3) | Algebraic variety |
| Keyword(4) | Sato's b function |
| 1st Author's Name | Sumio Watanabe |
| 1st Author's Affiliation | Advanced Information Processing Division P & I Laboratory, Tokyo Institute of Technology() |
| Date | 1998/11/17 |
| Paper # | NC98-64 |
| Volume (vol) | vol.98 |
| Number (no) | 401 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |