| Presentation | 2010-01-18 Sequential Learning and Model Selection under Unstable Environments Koichiro YAMAUCHI, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this research, an weighted error function for the learning of RBFNN under virtual concept drift environments is proposed. Under such environments, the prior distribution of learning samples is changing over time so that online learning tasks usually cause catastrophic forgetting. Such environments are parts of covariate shift. First of all, a statistical model of such environments is constructed. Then, we applied the learning strategies under covariate-shift using the statistical model. Moreover, a weighted Automatic Relevance Detection (ARD) is derived to calculate the predictive distribution of output values. The method also provides the model selection criterion. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Sequential Learning / unstable environments / Virtual Concept Drift / Radial Basis Function Neural Network (RBFNN) / Generalization capability / Student's-t distribution |
| Paper # | NC2009-75 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2010/1/11(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Vice Chair | |
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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) | Sequential Learning and Model Selection under Unstable Environments |
| Sub Title (in English) | |
| Keyword(1) | Sequential Learning |
| Keyword(2) | unstable environments |
| Keyword(3) | Virtual Concept Drift |
| Keyword(4) | Radial Basis Function Neural Network (RBFNN) |
| Keyword(5) | Generalization capability |
| Keyword(6) | Student's-t distribution |
| 1st Author's Name | Koichiro YAMAUCHI |
| 1st Author's Affiliation | Chubu University, Department of Information Science() |
| Date | 2010-01-18 |
| Paper # | NC2009-75 |
| Volume (vol) | vol.109 |
| Number (no) | 363 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |