DocumentCode
2227036
Title
Approximation Algorithms Using Hierarchies of Semidefinite Programming Relaxations
Author
Chlamtac, Eden
Author_Institution
Princeton Univ., Princeton
fYear
2007
fDate
21-23 Oct. 2007
Firstpage
691
Lastpage
701
Abstract
We. introduce, a framework for studying semidefiniie programming (SOP) relaxations based on the Lasserre hierarchy in the context of approximation algorithms for combinatorial problems. As an application of our approach, we give, improved approximation algorithms for two problems. We show that for some fixed constant epsiv > 0, given a 3-uniform hypergraph containing an independent set of size (1/2 - epsiv)v, we can find an independent set of size Omega(nepsiv). This improves upon the result of Krivelevich, Nathaniel and Sitdakov, who gave an algorithm finding an independent set of size Omega(n6gamma-3) for hypergraphs with an independent set of size gamman (but no guarantee for gamma les 1/2). We also give an algorithm which finds an O(n0.2072)-coloring given a 3-colorable graph, improving upon the work of Aurora, Clamtac and Charikar. Our approach stands in contrast to a long series of inapproximability results in the Lovasz Schrijver linear programming (LP) and SDP hierarchies for other problems.
Keywords
approximation theory; graph colouring; linear programming; relaxation theory; set theory; 3-colorable hypergraph; Lasserre hierarchy; Lovasz Schrijver linear programming; approximation algorithm; combinatorial problem; linear programming; semidefinite programming relaxation; set theory; Algorithm design and analysis; Application software; Approximation algorithms; Computer science; Design optimization; Electronic mail; Law; Legal factors; Linear programming; Polynomials;
fLanguage
English
Publisher
ieee
Conference_Titel
Foundations of Computer Science, 2007. FOCS '07. 48th Annual IEEE Symposium on
Conference_Location
Providence, RI
ISSN
0272-5428
Print_ISBN
978-0-7695-3010-9
Type
conf
DOI
10.1109/FOCS.2007.72
Filename
4389537
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