Presentation | 1995/7/27 Regularization Models with Multiple Hyperparameters and Applications Atsushi Matsui, Takashi Matsumoto, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The standard regularization theory converts ill-posed problems into parameterized family of minimization problems. A Bayesian approach is taken to derive conditions for optimal (multiple) hyperparameters and optimal regularizer. Examples are also given. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | standard regularization / ill-posed problem / bayesian inference / multiple hyperparameter |
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Committee | NC |
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Conference Date | 1995/7/27(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) | Regularization Models with Multiple Hyperparameters and Applications |
Sub Title (in English) | |
Keyword(1) | standard regularization |
Keyword(2) | ill-posed problem |
Keyword(3) | bayesian inference |
Keyword(4) | multiple hyperparameter |
1st Author's Name | Atsushi Matsui |
1st Author's Affiliation | Department of Electrical Engineering, Waseda University() |
2nd Author's Name | Takashi Matsumoto |
2nd Author's Affiliation | Department of Electrical Engineering, Waseda University |
Date | 1995/7/27 |
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Volume (vol) | vol.95 |
Number (no) | 189 |
Page | pp.pp.- |
#Pages | 8 |
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