191 search results - page 2 / 39 » Generalized Power Method for Sparse Principal Component Anal... |
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...
PKDD
2010
Springer
13 years 3 months ago
2010
Springer
Abstract. Principal component analysis (PCA) and its dual—principal coordinate analysis (PCO)—are widely applied to unsupervised dimensionality reduction. In this paper, we sho...
CVPR
2008
IEEE
13 years 11 months ago
2008
IEEE
Recently, 2DPCA and its variants have attracted much attention in face recognition area. In this paper, some efforts are made to discover the underlying fundaments of these method...
CORR
2012
Springer
12 years 1 months ago
2012
Springer
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
ECML
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...