110 search results - page 6 / 22 » Optimal kernel selection in Kernel Fisher discriminant analy... |
ICMLC
2010
Springer
13 years 6 months ago
2010
Springer
We review a multiple kernel learning (MKL) technique called p regularised multiple kernel Fisher discriminant analysis (MK-FDA), and investigate the effect of feature space denois...
ICPR
2008
IEEE
14 years 8 months ago
2008
IEEE
A Generalized Nonlinear Discriminant Analysis (GNDA) method is proposed, which implements Fisher discriminant analysis in a nonlinear mapping space. Linear discriminant analysis i...
CVPR
2007
IEEE
14 years 9 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...
JMLR
2006
13 years 7 months ago
2006
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
PAMI
2011
13 years 2 months ago
2011
— Kernel mapping is one of the most used approaches to intrinsically derive nonlinear classifiers. The idea is to use a kernel function which maps the original nonlinearly separ...