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
Conference Date 2008/11/20(1days)
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Registration To Media Experience and Virtual Environment (MVE)
Language JPN
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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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