Presentation | 1999/3/19 Independent Component Analysis by Geometric Optimization method Yasunori Nishimori, Shotaro Akaho, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Various problems arizing from signal processing, computer vision, and control theory can be regarded as opitimization problems on the orthogonal group. But when we apply ordinary iterative optimization methods such as the gradient descent method to those problems, the updated matrix deviates from the orthogonal group in each step. In order to circumvent this problem we propose a new geometric optimization method for the orthogonal group based on geodesics, and applied it to independent component analysis, which is a new statistical signal processing method making impact on a variety of fields. Simulation result shows our method accelerates the covergence of learning. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | ICA / gradient descent method / Newton method / Lie group / geodesics |
Paper # | NC98-161 |
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Committee | NC |
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Conference Date | 1999/3/19(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) | Independent Component Analysis by Geometric Optimization method |
Sub Title (in English) | |
Keyword(1) | ICA |
Keyword(2) | gradient descent method |
Keyword(3) | Newton method |
Keyword(4) | Lie group |
Keyword(5) | geodesics |
1st Author's Name | Yasunori Nishimori |
1st Author's Affiliation | Electrotechnical Laboratory() |
2nd Author's Name | Shotaro Akaho |
2nd Author's Affiliation | Electrotechnical Laboratory |
Date | 1999/3/19 |
Paper # | NC98-161 |
Volume (vol) | vol.98 |
Number (no) | 674 |
Page | pp.pp.- |
#Pages | 7 |
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