68 search results - page 2 / 14 » Testing for Homogeneity with Kernel Fisher Discriminant Anal... |
ECCV
2006
Springer
14 years 7 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...
ICDM
2009
IEEE
14 years 1 days ago
2009
IEEE
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
FGR
2004
IEEE
13 years 9 months ago
2004
IEEE
The null space-based LDA takes full advantage of the null space while the other methods remove the null space. It proves to be optimal in performance. From the theoretical analysi...
ECCV
2004
Springer
13 years 10 months ago
2004
Springer
The null space of the within-class scatter matrix is found to express most discriminative information for the small sample size problem (SSSP). The null space-based LDA takes full ...
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...