This paper presents a scheme for unsupervised classification with Gaussian mixture models by means of statistical learning analysis. A Bayesian Ying-Yang harmony learning system a...
We present a mixture model whose components are Restricted Boltzmann Machines (RBMs). This possibility has not been considered before because computing the partition function of a...
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
Abstract--In this paper, we (1) provide a complete framework for classification using Variational Mixture of Experts (VME); (2) derive the variational lower bound; and (3) apply th...