Recently there has been interest in the use of classifiers based on the product of experts (PoE) framework. PoEs offer an alternative to the standard mixture of experts (MoE) fram...
We propose a more efficient version of the slice sampler for Dirichlet process mixture models described by Walker (2007). This sampler allows the fitting of infinite mixture mod...
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Abstract. Classifiers based on Gaussian mixture models are good performers in many pattern recognition tasks. Unlike decision trees, they can be described as stable classifier: a s...
Jonas Richiardi, Andrzej Drygajlo, Laetitia Todesc...
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...