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...
A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP...
Abstract. Portfolios of assets whose returns have the Gaussian mixture distribution are optimized in the static setting to find portfolio weights and efficient frontiers using the ...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...