11 search results - page 1 / 3 » Learning the kernel matrix in discriminant analysis via quad... |
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...
JMLR
2008
13 years 4 months ago
2008
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
ICASSP
2007
IEEE
13 years 11 months ago
2007
IEEE
Abstract— This work considers a combination classificationregression based framework with the proposal of using learned kernels in modified support vector regression to provide...
PR
2008
13 years 4 months ago
2008
It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...
IJCNN
2006
IEEE
13 years 10 months ago
2006
IEEE
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...