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146
Voted
SIAMMAX
2010
14 years 10 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...
136
Voted
CVPR
2005
IEEE
16 years 3 months ago
2005
IEEE
A novel framework called 2D Fisher Discriminant Analysis
(2D-FDA) is proposed to deal with the Small Sample
Size (SSS) problem in conventional One-Dimensional Linear
Discriminan...
105
Voted
CVPR
2009
IEEE
15 years 10 months ago
2009
IEEE
Linear discriminant analysis (LDA) has been successfully applied into computer vision and pattern recognition for effective feature extraction. High-dimensional objects such as im...
143
Voted
ACML
2009
Springer
15 years 10 months ago
2009
Springer
In this paper, we propose a Robust Discriminant Analysis based on maximum entropy (MaxEnt) criterion (MaxEnt-RDA), which is derived from a nonparametric estimate of Renyi’s quadr...
146
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SDM
2008
SIAM
15 years 5 months ago
2008
SIAM
We describe a fast algorithm for kernel discriminant analysis, empirically demonstrating asymptotic speed-up over the previous best approach. We achieve this with a new pattern of...