TY - GEN
T1 - Loop calculus for satisfiability
AU - Kroc, Lukas
AU - Chertkov, Michael
PY - 2008
Y1 - 2008
N2 - 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.,
AB - 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.,
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M3 - Conference contribution
AN - SCOPUS:57749118694
SN - 9781577353683
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 1810
EP - 1811
BT - AAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference
T2 - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08
Y2 - 13 July 2008 through 17 July 2008
ER -