Statistical and computational concerns have motivated parameter estimators based on various forms of likelihood, e.g., joint, conditional, and pseudolikelihood. In this paper, we ...
Multi-reference frame motion estimation improves the accuracy of motion compensation in video compression, but it also dramatically increases computational complexity. Based on tr...
In this paper we present an approach to performance estimation for hard real-time systems. We consider architectures consisting of multiple processors. The scheduling policy is ba...
We propose a simulation-based method for calculating maximum likelihood estimators in latent variable models. The proposed method integrates a recently developed sampling strategy...
We introduce an algorithm that simultaneously estimates a classification function as well as its gradient in the supervised learning framework. The motivation for the algorithm is...