921 search results - page 13 / 185 » Kernel Principal Component Analysis |
NIPS
2008
13 years 9 months ago
2008
We analyse matching pursuit for kernel principal components analysis (KPCA) by proving that the sparse subspace it produces is a sample compression scheme. We show that this bound...
ICIAR
2004
Springer
14 years 28 days ago
2004
Springer
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
SAS
2010
Springer
13 years 6 months ago
2010
Springer
Numerical Abstract Domains via Principal Component Analysis Gianluca Amato, Maurizio Parton, and Francesca Scozzari Universit`a di Chieti-Pescara – Dipartimento di Scienze We pro...
ICONIP
2007
13 years 9 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...