Bayesian analysis is a popular subspace based face recognition method. It casts the face recognition task into a binary classification problem with each of the two classes, intrap...
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
Abstract. In this paper, the authors address the permutation ambiguity that exists in frequency domain Independent Component Analysis of convolutive mixtures. Many methods have bee...
Probability distributions are central tools for probabilistic modeling in data mining, and they lack in functional data analysis (FDA). In this paper we propose a probability dist...
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...