Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
Over the years, many Linear Discriminant Analysis (LDA) algorithms have been proposed for the study of high dimensional data in a large variety of problems. An intrinsic limitatio...
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
Abstract. We study discriminative joint density models, that is, generative models for the joint density p(c, x) learned by maximizing a discriminative cost function, the condition...
This paper introduces a novel nonlinear extension of Fisher's classical linear discriminant analysis (FDA) known as high-order Fisher's discriminant analysis (HOFDA). Th...