| Presentation | 2008-06-27 GA-based geometrical learning of binary neural networks and its generalization capability Syuhei SHIMADA, Hidehiro NAKANO, Arata MIYAUCHI, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | GA-based geometrical learning of Binary Neural Network (BNN) is discussed in this paper. To apply BNN to the multi class separation problems, we propose two learning methods for multi bit output BNN. The first method learns the teacher signals corresponding to each class in parallel. The second method learns them seqencially. Performing numerical experiments for a basic multi class separation problem, the leaning performances of the generalization capability and the number of hidden-layer neurons in each method are compared. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Binary Neural Network / Genetic algorithm / Supervised learning / Geometrical learning / Generalization capability |
| Paper # | NC2008-27 |
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| Committee | NC |
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| Conference Date | 2008/6/19(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) | GA-based geometrical learning of binary neural networks and its generalization capability |
| Sub Title (in English) | |
| Keyword(1) | Binary Neural Network |
| Keyword(2) | Genetic algorithm |
| Keyword(3) | Supervised learning |
| Keyword(4) | Geometrical learning |
| Keyword(5) | Generalization capability |
| 1st Author's Name | Syuhei SHIMADA |
| 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 | 2008-06-27 |
| Paper # | NC2008-27 |
| Volume (vol) | vol.108 |
| Number (no) | 101 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |