EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
A novel objective full-reference image quality assessment metric based on symmetric geometric moments (SGM) is proposed. SGM is used to represent the structural information in the...
We present a simple and efficient entropy coder that combines run-length and Golomb-Rice encoders. The encoder automatically switches between the two modes according to simple rul...
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...