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Every 2-CSP Allows Nontrivial Approximation
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0002-5379-345X
2005 (English)In: Proceedings of the 37th Annual ACM Symposium on Theory of Computing, 2005, 740-746 p.Conference paper (Refereed)
Abstract [en]

We use semidefinite programming to prove that any constraint satisfaction problem in two variables over any domain allows an efficient approximation algorithm that does provably better than picking a random assignment. To be more precise assume that each variable can take values in [d] and that each constraint rejects t out of the d2 possible input pairs. Then, for some universal constant c, we can, in probabilistic polynomial time, find an assignment whose objective value is, on expectation, within a factor (1- t/d2(1- c/d2 log d)) of optimal.

Place, publisher, year, edition, pages
2005. 740-746 p.
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-63001DOI: 10.1145/1060590.1060700ScopusID: 2-s2.0-26944485593ISBN: 1-58113-960-8OAI: diva2:481480
the 37th Annual ACM Symposium on Theory of Computing
QC 20120123Available from: 2012-01-21 Created: 2012-01-21 Last updated: 2012-01-23Bibliographically approved

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Håstad, Johan
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