Loop Calculus, introduced by Chertkov and Chernyak, is a new technique to incrementally improve approximations computed by Loopy Belief Propagation (LBP), with the ability to even...
Bayesian belief networks have grown to prominence because they provide compact representations of many domains, and there are algorithms to exploit this compactness. The next step...
A new incremental knowledge acquisition approach for the effective development of efficient problem solvers for combinatorial problems based on probabilistic search algorithms is ...
This paper presents a probabilistic event-driven fault localization technique, which uses a probabilistic symptomfault map as a fault propagation model. The technique isolates the...
Most probabilistic inference algorithms are specified and processed on a propositional level. In the last decade, many proposals for algorithms accepting first-order specificat...