414 search results - page 2 / 83 » Kernel Optimization in Discriminant Analysis |
CVPR
2005
IEEE
14 years 7 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...
CVPR
2007
IEEE
14 years 7 months ago
2007
IEEE
Discriminant Analysis (DA) methods have demonstrated their utility in countless applications in computer vision and other areas of research ? especially in the C class classificat...
ICPR
2004
IEEE
14 years 6 months ago
2004
IEEE
Mika et al. [3] introduce a non-linear formulation of Fisher's linear discriminant, based the now familiar "kernel trick", demonstrating state-of-the-art performanc...
JMLR
2008
13 years 5 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...
CVPR
2005
IEEE
14 years 7 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...