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AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
15 years 6 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
15 years 2 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
88
Voted
CSDA
2006
87views more  CSDA 2006»
14 years 11 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
16 years 1 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»
14 years 11 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