| Presentation | 1997/2/7 Second-order Learning Algorithm with Squared Penalty Term Kazumi Saito, Ryohei Nakano, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper compares three penalty terms with respect to the efficiency of supervised learning, by using first- and second-order learning algorithms. Our experiments,showed that for a reasonably adequate penalty factor, the combination of the squared penalty term and the second-order learning algorithm drastically improves the convergence performance more than 20 times over the other combinations, at the same time bringing about better generalization performance. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | penalty term / second-order learning algorithm / generalization performance / conver-gence performance. |
| Paper # | NLP96-151,NC96-105 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1997/2/7(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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| Vice Chair | |
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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) | Second-order Learning Algorithm with Squared Penalty Term |
| Sub Title (in English) | |
| Keyword(1) | penalty term |
| Keyword(2) | second-order learning algorithm |
| Keyword(3) | generalization performance |
| Keyword(4) | conver-gence performance. |
| 1st Author's Name | Kazumi Saito |
| 1st Author's Affiliation | NTT Communication Science Laboratories() |
| 2nd Author's Name | Ryohei Nakano |
| 2nd Author's Affiliation | NTT Communication Science Laboratories |
| Date | 1997/2/7 |
| Paper # | NLP96-151,NC96-105 |
| Volume (vol) | vol.96 |
| Number (no) | 512 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |