191 search results - page 11 / 39 » Generalized Power Method for Sparse Principal Component Anal... |
108
Voted
ESANN
2003
15 years 1 months ago
2003
Abstract. We focus on covariance criteria for finding a suitable subspace for regression in a reproducing kernel Hilbert space: kernel principal component analysis, kernel partial...
ICIP
2008
IEEE
15 years 6 months ago
2008
IEEE
—Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms usi...
93
Voted
ICPR
2010
IEEE
15 years 1 months ago
2010
IEEE
Canonical correlation analysis (CCA) is a powerful tool for analyzing multi-dimensional paired data. However, CCA tends to perform poorly when the number of paired samples is limit...
117
Voted
AAAI
2008
15 years 2 months ago
2008
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
ICDM
2007
IEEE
15 years 3 months ago
2007
IEEE
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...