| Presentation | 1998/5/25 Improving the Generalization Ability of the Minimum Classification Error Learning and Its Application to Neural Networks Jun ROKUI, Hiroshi SHIMODAIRA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning proposed by Katagiri and Juang in 1992 has receive much attention because of its good recognition performance and wide range of applications including the case where the length of feature vectors is not fixed as in the case of speech recognition. In this report, we propose a new method to improve the generalization ability of the MCE learning by employing an regularization technique which is widely used to solve ill-posed problems. Feed-forward neural networks are employed to evaluate the performance of the proposed method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | GPD / MCE / generalization / over-fitting / regularization |
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| Committee | NC |
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| Conference Date | 1998/5/25(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| 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) | Improving the Generalization Ability of the Minimum Classification Error Learning and Its Application to Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | GPD |
| Keyword(2) | MCE |
| Keyword(3) | generalization |
| Keyword(4) | over-fitting |
| Keyword(5) | regularization |
| 1st Author's Name | Jun ROKUI |
| 1st Author's Affiliation | School of Information Science, Japan Advanced Institute of Science and Technology() |
| 2nd Author's Name | Hiroshi SHIMODAIRA |
| 2nd Author's Affiliation | School of Information Science, Japan Advanced Institute of Science and Technology |
| Date | 1998/5/25 |
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| Volume (vol) | vol.98 |
| Number (no) | 77 |
| Page | pp.pp.- |
| #Pages | 7 |
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