52 search results - page 1 / 11 » Fisher Kernel Criterion for Discriminant Analysis |
CVPR
2005
IEEE
14 years 6 months ago
2005
IEEE
We simultaneously approach two tasks of nonlinear discriminant analysis and kernel selection problem by proposing a unified criterion, Fisher+Kernel Criterion. In addition, an eff...
ECCV
2006
Springer
14 years 6 months ago
2006
Springer
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
PR
2007
13 years 4 months ago
2007
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
CVPR
2005
IEEE
13 years 10 months ago
2005
IEEE
This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Mac...
CVPR
2005
IEEE
14 years 6 months ago
2005
IEEE
It was prescriptive that an image matrix was transformed into a vector before the kernel-based subspace learning. In this paper, we take the Kernel Discriminant Analysis (KDA) alg...