Presentation | 1998/2/6 Dynamic function approximation by online EM algorithm Shin Ishii, Masa-aki Sato, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this research report, we propose an online EM algorithm for Normalized Gaussian Network which is composed of normalized Gaussian functions with linear coefficients. A regularization method to deal with singular input distribution, and unit creation-deletion mechanisms are also discussed. Our approach is suitable for dynamical environments where the input-output distribution of data changes in time. A computer simulation is done for a reinforcement learning problem; the result is encouraging. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | EM algorithm / Online learning / Radial basis functions / Stochastic model / Dynamic function approximation / Reinforcement learning |
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Conference Information | |
Committee | NLP |
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Conference Date | 1998/2/6(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Dynamic function approximation by online EM algorithm |
Sub Title (in English) | |
Keyword(1) | EM algorithm |
Keyword(2) | Online learning |
Keyword(3) | Radial basis functions |
Keyword(4) | Stochastic model |
Keyword(5) | Dynamic function approximation |
Keyword(6) | Reinforcement learning |
1st Author's Name | Shin Ishii |
1st Author's Affiliation | Nara Institute of Science and Technology() |
2nd Author's Name | Masa-aki Sato |
2nd Author's Affiliation | ATR Human Information Processing Research Laboratories |
Date | 1998/2/6 |
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Volume (vol) | vol.97 |
Number (no) | 531 |
Page | pp.pp.- |
#Pages | 8 |
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