Randomized Algorithms for the Loop Cutset Problem
نویسندگان
چکیده
منابع مشابه
Randomized Algorithms for the Loop Cutset Problem
We show how to nd a minimum weight loop cutset in a Bayesian network with high probability. Finding such a loop cutset is the rst step in the method of conditioning for inference. Our randomized algorithm for nding a loop cutset outputs a minimum loop cutset after O(c 6kn) steps with probability at least 1 (1 1 6k ) k , where c > 1 is a constant speci ed by the user, k is the minimal size of a ...
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We show how to find a small loop cutset in a Bayesian network. Finding such a loop cutset is the first step in the method of conditioi~ing for inference. Our algorithm for finding a loop cutset, called MGA, finds a loop cutset which is guaranteed in the worst case to contain less than twice the number of variables contained in a minimum loop cutset. We test MGA on randomly generated graphs and ...
متن کاملRandom Algorithms for the Loop Cutset Problem
We show how to find a minimum loop cutset in a Bayesian network with high probability. Finding such a loop cutset is the first step in Pearl's method of conditioning for inference. Our random algorithm for finding a loop cutset, called REPEATEDWGUESSI, outputs a minimum loop cutset, after O(c.6"n) steps, with probability a t least 1 (1 $ ) c ~ * , where c > 1 is a constant specified by the user...
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The LOOP CUTSET problem was historically posed by Pearl as a subroutine in Pearl’s algorithm for computing inference in probabilistic networks. The efficiency of the algorithm that solves the probabilistic inference highly depends on the size of the smallest known LOOP CUTSET. This justifies the search for exact algorithms for finding a minimum LOOP CUTSET. In this thesis we are investigating t...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 2000
ISSN: 1076-9757
DOI: 10.1613/jair.638