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AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
14 years 2 months ago
A Discriminant Analysis for Undersampled Data
One of the inherent problems in pattern recognition is the undersampled data problem, also known as the curse of dimensionality reduction. In this paper a new algorithm called pai...
Matthew Robards, Junbin Gao, Philip Charlton
ICPR
2010
IEEE
13 years 11 months ago
A Discriminative and Heteroscedastic Linear Feature Transformation for Multiclass Classification
This paper presents a novel discriminative feature transformation, named full-rank generalized likelihood ratio discriminant analysis (fGLRDA), on the grounds of the likelihood ra...
Hung-Shin Lee, Hsin-Min Wang, Berlin Chen
CSDA
2006
87views more  CSDA 2006»
13 years 8 months ago
Choice of B-splines with free parameters in the flexible discriminant analysis context
Flexible discriminant analysis (FDA) is a general methodology which aims at providing tools for multigroup non linear classification. It consists in a nonparametric version of dis...
Christelle Reynès, Robert Sabatier, Nicolas...
ICIP
2004
IEEE
14 years 10 months ago
Sparse representation of images with hybrid linear models
We propose a mixture of multiple linear models, also known as hybrid linear model, for a sparse representation of an image. This is a generalization of the conventional KarhunenLo...
Kun Huang, Allen Y. Yang, Yi Ma
PAMI
2008
162views more  PAMI 2008»
13 years 8 months ago
Dimensionality Reduction of Clustered Data Sets
We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
Guido Sanguinetti