| Presentation | 1999/10/21 Regularization Term of Multi Layer Perceptrons Masato UCHIDA, Hiroyuki SHIOYA, Tsutomu DA-TE, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Learning methods adding a regularization term to a loss function to be minimized has been proposed for training multi layer perceptrons, in order to avoid overfitting, improve predictive performance, or perform structurization. In this paper, a learning algoithm with non-Bayesian regularization term whose scaduling parameter doesn't become a constant is derived based on a framework of the parametric estimation. The proposed model is remarkable becase the reguralization term can be regarded as a variance of the model if quadratic loss function is used as a loss function. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Regularization term / learning of multi layer perceptrons |
| Paper # | NC99-44 |
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| Committee | NC |
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| Conference Date | 1999/10/21(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) | Regularization Term of Multi Layer Perceptrons |
| Sub Title (in English) | |
| Keyword(1) | Regularization term |
| Keyword(2) | learning of multi layer perceptrons |
| 1st Author's Name | Masato UCHIDA |
| 1st Author's Affiliation | Faculty of Engineering, Hokkaido University() |
| 2nd Author's Name | Hiroyuki SHIOYA |
| 2nd Author's Affiliation | Faculty of Engineering, Hokkaido University |
| 3rd Author's Name | Tsutomu DA-TE |
| 3rd Author's Affiliation | Faculty of Engineering, Hokkaido University |
| Date | 1999/10/21 |
| Paper # | NC99-44 |
| Volume (vol) | vol.99 |
| Number (no) | 382 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |