We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
In this paper we present a fast method for computing acoustic likelihoods that makes use of a Graphics Processing Unit (GPU). After enabling the GPU acceleration the main processo...
We investigate the problem of source separation in images in the Bayesian framework using the color channel dependencies. As a case in point we consider the source separation of co...
Copyright 2001 IEEE. Published in the 2001 International Conference on Image Processing (ICIP-2001), October 7-10, 2001, Thessaloniki, Greece. Personal use of this material is per...
Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...