We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
This paper proposes a new analytical method for estimating parameters of a homogeneous isotropic Potts model with an asymmetric Gibbs potential function. The model is generalized ...
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
In this paper we present a novel approach for estimating featurespace maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maxim...
Arnab Ghoshal, Daniel Povey, Mohit Agarwal, Pinar ...
Abstract. We proposed recently a new method for separating linearquadratic mixtures of independent real sources, based on parametric identification of a recurrent separating struc...