847 search results - page 10 / 170 » HITS is Principal Components Analysis |
119
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ICIP
2005
IEEE
15 years 6 months ago
2005
IEEE
This paper presents a view independent face recognition method based on kernel principal component analysis (KPCA) of local parts. View changes induce large variation in feature s...
116
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COLT
2004
Springer
15 years 5 months ago
2004
Springer
The main goal of this paper is to prove inequalities on the reconstruction error for Kernel Principal Component Analysis. With respect to previous work on this topic, our contribu...
103
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NIPS
2008
15 years 1 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
97
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PAMI
2008
15 years 9 days ago
2008
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...
COLT
2010
Springer
14 years 10 months ago
2010
Springer
We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of obse...