| Presentation | 1996/12/14 Optimal Realization of Optimally Generalizing Neural Networks Shinsuke NAKAZAWA, Hidemitsu OGAWA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Learning in a multilayered feedforward neural network is equivalent to finding an optimal function from the given set of training data, based on some optimization criterion. In the previous work, one of the authors gave a method of realizing a neural network which satisfies a criterion for generalization. In that realization, it was shown that there exists infinite freedom in the method of selecting the number of hidden units, basis functions, and weights parameters. In this paper, using the above mentioned degree of freedom, we obtain a realization of a neural network which is resistant to errors and faults in the hardware, while maintaining the generalization ablility. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | neural network / generalization / fault tolerance / connectlion fault / minimum error realization |
| Paper # | NC96-60 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1996/12/14(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) | Optimal Realization of Optimally Generalizing Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | neural network |
| Keyword(2) | generalization |
| Keyword(3) | fault tolerance |
| Keyword(4) | connectlion fault |
| Keyword(5) | minimum error realization |
| 1st Author's Name | Shinsuke NAKAZAWA |
| 1st Author's Affiliation | Department of Computer Science Graduate School of Information Science and Engineering Tokyo Institute of Technology() |
| 2nd Author's Name | Hidemitsu OGAWA |
| 2nd Author's Affiliation | Department of Computer Science Graduate School of Information Science and Engineering Tokyo Institute of Technology |
| Date | 1996/12/14 |
| Paper # | NC96-60 |
| Volume (vol) | vol.96 |
| Number (no) | 430 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |