Presentation | 1996/3/18 On Bayes Optimal Prediction based on Mixture Model of Multilayer Neural Networks Hiroki Hashikawa, Masayuki Gotoh, Nobuhiko Tawara, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In learning of the probabilistic models, it is important to predict accurately for the output of future observation. On prediction of the future observation, it is not necessary to select a particular model from the model class. The objective here is to predict the output of the future observations accurately. On the other hand, a lot of researches of the prediction methods based on Bayes decision theory for the probabilistic models have been reported. These Bayesian methods are efficient to the prediction with accuracy. In this paper, we, at first, show that the prediction using the mixture model of all neural network models in the model class is bayes optimal. However, this mixture model is difficult to calculate strictly for neural network models, since the complex integration on the parameter space is cannot be calculated for the general priors. We, therefore, propose the new prediction method with asymptotic Bayes optimality, based on Laplacian method which calculates the asymptotic posterior predictive distribution and then removes the integration, apply this method to the multilayer neural network models and verify the efficiency of the proposal through the simulation experiments. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Neural Network / Bayes Decision Theory / Mixture Model / Generalization |
Paper # | NC-95-121 |
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Committee | NC |
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Conference Date | 1996/3/18(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) | On Bayes Optimal Prediction based on Mixture Model of Multilayer Neural Networks |
Sub Title (in English) | |
Keyword(1) | Neural Network |
Keyword(2) | Bayes Decision Theory |
Keyword(3) | Mixture Model |
Keyword(4) | Generalization |
1st Author's Name | Hiroki Hashikawa |
1st Author's Affiliation | Musashi Institute of Technology() |
2nd Author's Name | Masayuki Gotoh |
2nd Author's Affiliation | Waseda University |
3rd Author's Name | Nobuhiko Tawara |
3rd Author's Affiliation | Musashi Institute of Technology |
Date | 1996/3/18 |
Paper # | NC-95-121 |
Volume (vol) | vol.95 |
Number (no) | 598 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |