"Constraint satisfaction is a general problem in which the goal is to find values for a set of variables that will satisfy a given set of constraints. It is the core of many a...
We wish to recover an original image u from several blurry-noisy versions fk, called frames. We assume a more severe degradation model, in which the image u has been blurred by a ...
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
Abstract. We consider the framework of stochastic multi-armed bandit problems and study the possibilities and limitations of strategies that explore sequentially the arms. The stra...