| Presentation | 1994/3/25 Error analysis and training data arrangement for neural networks Kenji Fukumizu, Sumio Watanabe, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper discusses the error of function approximation neural networks,when they approximate an unknown system which can give a response to an arbitrary input,such as in some system identification problems.In this case,we can choose an input distribution to obtain training data different from the one giving input data in the actual environment.Applying the statistical asymptotic theory,we elucidate which input distribution for training minimizes the mean squared error in the actual environment.Based on this analysis a novel algorithm to obtain training data is proposed,and its effect is verified by computer simulations. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | neural network / parametric estimation / statistical learning / statistical asymptotic theory |
| Paper # | NC93-126 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1994/3/25(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) | Error analysis and training data arrangement for neural networks |
| Sub Title (in English) | |
| Keyword(1) | neural network |
| Keyword(2) | parametric estimation |
| Keyword(3) | statistical learning |
| Keyword(4) | statistical asymptotic theory |
| 1st Author's Name | Kenji Fukumizu |
| 1st Author's Affiliation | Information and Communication Research and Development Center, Ricoh Co.,Ltd.() |
| 2nd Author's Name | Sumio Watanabe |
| 2nd Author's Affiliation | Information and Communication Research and Development Center, Ricoh Co.,Ltd. |
| Date | 1994/3/25 |
| Paper # | NC93-126 |
| Volume (vol) | vol.93 |
| Number (no) | 537 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |