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KDD
2006
ACM
149views Data Mining» more  KDD 2006»
14 years 5 months ago
Regularized discriminant analysis for high dimensional, low sample size data
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Jieping Ye, Tie Wang
ICCV
2007
IEEE
13 years 8 months ago
Probabilistic Linear Discriminant Analysis for Inferences About Identity
Many current face recognition algorithms perform badly when the lighting or pose of the probe and gallery images differ. In this paper we present a novel algorithm designed for th...
Simon J. D. Prince, James H. Elder
CVPR
2005
IEEE
14 years 6 months ago
Graph Embedding: A General Framework for Dimensionality Reduction
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
Shuicheng Yan, Dong Xu, Benyu Zhang, HongJiang Zha...
ICPR
2008
IEEE
14 years 6 months ago
Generalized Nonlinear Discriminant Analysis
A Generalized Nonlinear Discriminant Analysis (GNDA) method is proposed, which implements Fisher discriminant analysis in a nonlinear mapping space. Linear discriminant analysis i...
Hua Zhang, Li Zhang, Licheng Jiao, Weida Zhou
NECO
2000
190views more  NECO 2000»
13 years 4 months ago
Generalized Discriminant Analysis Using a Kernel Approach
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
G. Baudat, Fatiha Anouar