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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorBodlaender, H.L.
dc.contributor.authorTimmer, S.T.
dc.date.accessioned2012-08-24T17:01:08Z
dc.date.available2012-08-24
dc.date.available2012-08-24T17:01:08Z
dc.date.issued2012
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/14989
dc.description.abstractThe 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 find- ing a minimum LOOP CUTSET. In this thesis we are investigating the algorithmic complexity of the problem. We will look at both the unparameterized problem and the problem parameterized by the treewidth of the input graph. For both we give an exact exponential time algorithm. The running times of these algorithms are O(1.7548n ) and O(4tw ) respectively, where tw is the treewidth of the input graph. Finally, we prove a lower bound of 3tw for the parameterized problem.
dc.description.sponsorshipUtrecht University
dc.language.isoen
dc.titleExact Algorithms for Loop Cutset
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsLOOP CUTSET, MAXIMUM INDUCED FOREST, Exact Algorithms, Treewidth, Cut & Count, Branch & Bound, Branch & Reduce, FEEDBACK VERTEX SET
dc.subject.courseuuComputing Science


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