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...
This paper presents a novel discriminative feature transformation, named full-rank generalized likelihood ratio discriminant analysis (fGLRDA), on the grounds of the likelihood ra...
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...
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...
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...