Loop Calculus for Satisfiability

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Loop Calculus for Satisfiability
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 eventually make them exact. In this extended abstract, we give a brief overview of this technique, and show its relevance to the AI community. We consider the problem of Boolean Satisfiability (SAT) and use LBP with Loop Calculus corrections to perform probabilistic inference about the problem. In this preliminary work, we focus on identifying the main issues encountered when applying Loop Calculus, and include initial empirical results in the SAT domain.
Lukas Kroc, Michael Chertkov
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2008
Where AAAI
Authors Lukas Kroc, Michael Chertkov
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