In many applications non-stationary Gaussian or stationary nonGaussian noises can be observed. In this paper we present a maximum a posteriori estimation jointly of spectral ampli...
In a Bayesian network with continuous variables containing a variable(s) that is a conditionally deterministic function of its continuous parents, the joint density function for t...
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Mixture models, such as Gaussian Mixture Model, have been widely used in many applications for modeling data. Gaussian mixture model (GMM) assumes that data points are generated fr...
Abstract. It has been recently demonstrated that the classical EM algorithm for learning Gaussian mixture models can be successfully implemented in a decentralized manner by resort...
Nikos A. Vlassis, Yiannis Sfakianakis, Wojtek Kowa...