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
Link To Document :
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