Presentation | 1999/7/19 Model Comparisons and Predictions for Hierarchical Bayesian Neural Nets : Quadratic Approximation vs. MCMC Y. Nakajima, M. Asano, Y. Nakada, T. Matsumoto, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | MCMC is used to perform model comparisons and compute predictive mean for Hierarchical Bayesian Neural Nets. The scheme is tested against two examples which show the fact that Quadratic Approximation for marginal likelihood is reasonably sound. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Quadratic Approximation / Hybrid Monte Carlo / Annealed Importance Sampling / Marginal likelihood / Model comparison |
Paper # | NC99-35 |
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Committee | NC |
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Conference Date | 1999/7/19(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 | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Model Comparisons and Predictions for Hierarchical Bayesian Neural Nets : Quadratic Approximation vs. MCMC |
Sub Title (in English) | |
Keyword(1) | Quadratic Approximation |
Keyword(2) | Hybrid Monte Carlo |
Keyword(3) | Annealed Importance Sampling |
Keyword(4) | Marginal likelihood |
Keyword(5) | Model comparison |
1st Author's Name | Y. Nakajima |
1st Author's Affiliation | Department of Electrical, Electronics and Computer Engineering, Waseda University() |
2nd Author's Name | M. Asano |
2nd Author's Affiliation | Department of Electrical, Electronics and Computer Engineering, Waseda University |
3rd Author's Name | Y. Nakada |
3rd Author's Affiliation | Department of Electrical, Electronics and Computer Engineering, Waseda University |
4th Author's Name | T. Matsumoto |
4th Author's Affiliation | Department of Electrical, Electronics and Computer Engineering, Waseda University |
Date | 1999/7/19 |
Paper # | NC99-35 |
Volume (vol) | vol.99 |
Number (no) | 193 |
Page | pp.pp.- |
#Pages | 7 |
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