19 search results - page 1 / 4 » Regularized linear and kernel redundancy analysis |
CSDA
2007
13 years 11 months ago
2007
Redundancy analysis (RA) is a versatile technique used to predict multivariate criterion variables from multivariate predictor variables. The reduced-rank feature of RA captures r...
ICML
2007
IEEE
14 years 12 months ago
2007
IEEE
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
TKDE
2008
13 years 11 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...
NIPS
2004
14 years 17 days ago
2004
This paper investigates the effect of Kernel Principal Component Analysis (KPCA) within the classification framework, essentially the regularization properties of this dimensional...
JMLR
2010
13 years 9 months ago
2010
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...