| Presentation | 2007-01-25 Adaptive Ridge Learning in Kernel Eigenspace and Its Model Selection Shun GOKITA, Masashi SUGIYAMA, Keisuke SAKURAI, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In order to obtain better learning results in supervised learning, it is important to choose model parameters appropriately. Model selection is usually carried out by preparing a finite set of model candidates, estimating a generalization error for each candidate, and choosing the best one from the candidates. If the number of candidates is increased in this procedure, the optimization quality may be improved. However, this in turn increases the computational cost. In this paper, we focus on a generalization error estimator called the regularized subspace information criterion and derive an analytic form of the optimal model parameter over a set of infinitely many model candidates. This allows us to maximize the optimization quality with the computational cost kept moderate. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | supervised learning / generalization error / model selection / regularized subspace information criterion |
| Paper # | NC2006-97 |
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| Committee | NC |
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| Conference Date | 2007/1/18(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 | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Adaptive Ridge Learning in Kernel Eigenspace and Its Model Selection |
| Sub Title (in English) | |
| Keyword(1) | supervised learning |
| Keyword(2) | generalization error |
| Keyword(3) | model selection |
| Keyword(4) | regularized subspace information criterion |
| 1st Author's Name | Shun GOKITA |
| 1st Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology() |
| 2nd Author's Name | Masashi SUGIYAMA |
| 2nd Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology |
| 3rd Author's Name | Keisuke SAKURAI |
| 3rd Author's Affiliation | Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology |
| Date | 2007-01-25 |
| Paper # | NC2006-97 |
| Volume (vol) | vol.106 |
| Number (no) | 500 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |