4 search results - page 1 / 1 » Kernel Uncorrelated and Regularized Discriminant Analysis: A... |
TKDE
2008
13 years 4 months ago
2008
Linear and kernel discriminant analyses are popular approaches for supervised dimensionality reduction. Uncorrelated and regularized discriminant analyses have been proposed to ove...
CVPR
2006
IEEE
14 years 6 months ago
2006
IEEE
Several kernel algorithms have recently been proposed for nonlinear discriminant analysis. However, these methods mainly address the singularity problem in the high dimensional fe...
JMLR
2006
13 years 4 months ago
2006
Dimensionality reduction is an important pre-processing step in many applications. Linear discriminant analysis (LDA) is a classical statistical approach for supervised dimensiona...
KDD
2007
ACM
14 years 5 months ago
2007
ACM
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...