—We present solutions to two problems that prevent the effective use of population-based algorithms in clustering problems. The first solution presents a new representation for ...
We present an extension to the Mixture of Experts (ME) model, where the individual experts are Gaussian Process (GP) regression models. Using an input-dependent adaptation of the ...
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations are assumed to follow a mixture of two Gaussian distributions. This GARCH model...
In this work, the problem of the estimation of parameters in case of mixtures of models composed by the sum of multiple Gaussians is considered. It will be shown how this estimati...
In this paper, we propose a new semi-supervised training method for Gaussian Mixture Models. We add a conditional entropy minimizer to the maximum mutual information criteria, whi...