We prove that if NP ⊆ BPP, i.e., if SAT is worst-case hard, then for every probabilistic polynomial-time algorithm trying to decide SAT, there exists some polynomially samplable ...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
This paper addresses the problem of tracking objects with complex motion dynamics or shape changes. It is assumed that some of the visual features detected in the image (e.g., edg...
The paper takes a fresh look at algorithms for maximizing expected utility over a set of policies, that is, a set of possible ways of reacting to observations about an uncertain s...
In this paper we propose a novel approach to the perceptual interpretation of building facades that combines shape grammars, supervised classification and random walks. Procedural...