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ICML
2003
IEEE
14 years 5 months ago
Kernel PLS-SVC for Linear and Nonlinear Classification
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
Roman Rosipal, Leonard J. Trejo, Bryan Matthews
IJPRAI
2010
109views more  IJPRAI 2010»
13 years 2 months ago
Disguised Discrimination of Locality-Based Unsupervised Dimensionality Reduction
: Many locality-based unsupervised dimensionality reduction (DR) algorithms have recently been proposed and demonstrated to be effective to a certain degree in some classification ...
Bo Yang, Songcan Chen
VLSISP
2002
139views more  VLSISP 2002»
13 years 4 months ago
A Modified Minimum Classification Error (MCE) Training Algorithm for Dimensionality Reduction
Dimensionality reduction is an important problem in pattern recognition. There is a tendency of using more and more features to improve the performance of classifiers. However, not...
Xuechuan Wang, Kuldip K. Paliwal
PAMI
2011
12 years 11 months ago
Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors
This paper proposes a general method for improving image descriptors using discriminant projections. Two methods based on Linear Discriminant Analysis have been recently introduce...
Hongping Cai, Krystian Mikolajczyk, Jiri Matas
CVPR
2006
IEEE
14 years 6 months ago
Learning Semantic Patterns with Discriminant Localized Binary Projections
In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is refor...
Shuicheng Yan, Tianqiang Yuan, Xiaoou Tang