46 search results - page 3 / 10 » Kernel quadratic discriminant analysis for small sample size... |
SIAMMAX
2010
13 years 2 months ago
2010
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
ICIP
2002
IEEE
14 years 9 months ago
2002
IEEE
Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition applications. It is well kno...
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
Latent Variable Models (LVM), like the Shared-GPLVM
and the Spectral Latent Variable Model, help mitigate over-
fitting when learning discriminative methods from small or
modera...
FGR
2004
IEEE
13 years 11 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...
KDD
2008
ACM
14 years 7 months ago
2008
ACM
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...