208 search results - page 14 / 42 » Robust Kernel Principal Component Analysis |
JMLR
2002
13 years 7 months ago
2002
We present a class of algorithms for independent component analysis (ICA) which use contrast functions based on canonical correlations in a reproducing kernel Hilbert space. On th...
ECCV
2002
Springer
14 years 9 months ago
2002
Springer
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
ICA
2007
Springer
14 years 1 months ago
2007
Springer
We present a robust algorithm for independent component analysis that uses the sum of marginal quadratic negentropies as a dependence measure. It can handle arbitrary source densit...
TIP
2011
13 years 2 months ago
2011
—This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions are based upon a dual formu...
PAMI
2012
11 years 10 months ago
2012
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...