Presentation | 2007-03-16 A learning algorithm of multi-bit Binary Neural Networks and its application to recognition systems SATOSHI Murayama, Hidehiro NAKANO, Arata MIYAUCHI, |
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Abstract(in English) | A geometrical learning has been proposed as a learning method of BNNs. However, geometrical learning is the learning method basically for 1-bit output BNN. That is, the study on learning method of multi-bit BNNs is not sufficient so far. In this paper, we propose a GA-based learning algorithm of multi-bit BNNs. The proposal method use a GA for evaluation of hidden neuron parameters of multi-bit BNNs. We consider an evaluation method of individuals of GA in order to suppress increase of redundant hidden neurons. In the numerical experiments, we evaluate the number of hidden neurons and recognition performance for multi-class classification problem. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Binary Neural Networks / Genetic algorithm / Supervised learning / Geometrical learning |
Paper # | NC2006-212 |
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Committee | NC |
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Conference Date | 2007/3/9(1days) |
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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) | A learning algorithm of multi-bit Binary Neural Networks and its application to recognition systems |
Sub Title (in English) | |
Keyword(1) | Binary Neural Networks |
Keyword(2) | Genetic algorithm |
Keyword(3) | Supervised learning |
Keyword(4) | Geometrical learning |
1st Author's Name | SATOSHI Murayama |
1st Author's Affiliation | Musashi Institute of Technology() |
2nd Author's Name | Hidehiro NAKANO |
2nd Author's Affiliation | Musashi Institute of Technology |
3rd Author's Name | Arata MIYAUCHI |
3rd Author's Affiliation | Musashi Institute of Technology |
Date | 2007-03-16 |
Paper # | NC2006-212 |
Volume (vol) | vol.106 |
Number (no) | 590 |
Page | pp.pp.- |
#Pages | 6 |
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