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» Regularized Discriminant Analysis, Ridge Regression and Beyo...
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JMLR
2010
143views more  JMLR 2010»
13 years 2 months ago
Regularized Discriminant Analysis, Ridge Regression and Beyond
Fisher linear discriminant analysis (FDA) and its kernel extension--kernel discriminant analysis (KDA)--are well known methods that consider dimensionality reduction and classific...
Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jor...
ICPR
2008
IEEE
14 years 1 months ago
Boosting performance for 2D Linear Discriminant Analysis via regression
Two Dimensional Linear Discriminant Analysis (2DLDA) has received much interest in recent years. However, 2DLDA could make pairwise distances between any two classes become signi´...
Nam Nguyen, Wanquan Liu, Svetha Venkatesh
CSDA
2007
128views more  CSDA 2007»
13 years 7 months ago
Regularized linear and kernel redundancy analysis
Redundancy analysis (RA) is a versatile technique used to predict multivariate criterion variables from multivariate predictor variables. The reduced-rank feature of RA captures r...
Yoshio Takane, Heungsun Hwang
ICCV
2007
IEEE
14 years 9 months ago
Spectral Regression for Efficient Regularized Subspace Learning
Subspace learning based face recognition methods have attracted considerable interests in recent years, including Principal Component Analysis (PCA), Linear Discriminant Analysis ...
Deng Cai, Xiaofei He, Jiawei Han
ICDE
2008
IEEE
203views Database» more  ICDE 2008»
14 years 8 months ago
Training Linear Discriminant Analysis in Linear Time
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. It has been widely used in many fields of information proces...
Deng Cai, Xiaofei He, Jiawei Han