Presentation | 2008-11-27 Kernel PCA based on the metric of the input space JUN FUJIKI, SHOTARO AKAHO, |
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Abstract(in English) | Original kernel principle component analysis is finding the principle subspace of the data from least squares estimation based on the metric of feature space. However, the paper proposes the method to find the principle subspace of the data from least squares estimation based on the metric of input space. The proposed method is efficient when the metric of input space is known. |
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Paper # | PRMU2008-121,MVE2008-70 |
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Committee | MVE |
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Conference Date | 2008/11/20(1days) |
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Registration To | Media Experience and Virtual Environment (MVE) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Kernel PCA based on the metric of the input space |
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1st Author's Name | JUN FUJIKI |
1st Author's Affiliation | National Institute of Advanced Industrial Science and Technology() |
2nd Author's Name | SHOTARO AKAHO |
2nd Author's Affiliation | National Institute of Advanced Industrial Science and Technology |
Date | 2008-11-27 |
Paper # | PRMU2008-121,MVE2008-70 |
Volume (vol) | vol.108 |
Number (no) | 328 |
Page | pp.pp.- |
#Pages | 6 |
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