40 search results - page 4 / 8 » Deflation Methods for Sparse PCA |
ICONIP
2007
13 years 8 months ago
2007
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
PR
2008
13 years 7 months ago
2008
Face Representation (FR) plays a typically important role in face recognition and methods such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have be...
AAAI
2008
13 years 9 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 ...
BMCBI
2010
13 years 7 months ago
2010
Background: Principal component analysis (PCA) has gained popularity as a method for the analysis of highdimensional genomic data. However, it is often difficult to interpret the ...
ECML
2007
Springer
14 years 1 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...