| Presentation | 2009-01-19 Node perturbation learning with noisy reference Tatsuya CHO, Kentaro KATAHIRA, Masato OKADA, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose a node perturbation learning with noisy reference signal. Recently, the method for node perturbation has investigated without consideration of noise in reference signal. In biological system, however, noise plays an essential role and neural activities are intrinsically noisy. In this paper, we analyze a node perturbation with noisy reference used with linear perceptron. Learning succeeds even with the noisy reference. Proposed learning scheme reduces residual error in factor of output units compared to the noiseless cases. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | noisy reference / node perturbation / stocastic gradient method / liner perceptron |
| Paper # | NC2008-89 |
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| Committee | NC |
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| Conference Date | 2009/1/12(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) | Node perturbation learning with noisy reference |
| Sub Title (in English) | |
| Keyword(1) | noisy reference |
| Keyword(2) | node perturbation |
| Keyword(3) | stocastic gradient method |
| Keyword(4) | liner perceptron |
| 1st Author's Name | Tatsuya CHO |
| 1st Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo() |
| 2nd Author's Name | Kentaro KATAHIRA |
| 2nd Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo:RIKEN Brain Science Institute |
| 3rd Author's Name | Masato OKADA |
| 3rd Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo:RIKEN Brain Science Institute |
| Date | 2009-01-19 |
| Paper # | NC2008-89 |
| Volume (vol) | vol.108 |
| Number (no) | 383 |
| Page | pp.pp.- |
| #Pages | 5 |
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