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Approximation Algorithms Using Hierarchies of Semidefinite Programming Relaxations

机译:使用SEMIDEFINITE编程放松的层次结构的近似算法

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We introduce a framework for studying semidefinite programming (SDP) 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 ε>0, given a 3-uniform hypergraph containing an independent set of size ((1/2)-ε)n, we can find an independent set of size Ω(n{sup}ε). This improves upon the result of Krivelevich, Nathaniel and Sudakov, who gave an algorithm finding an independent set of size Ω{top}~(n{sup}(6r-3)) for hypergraphs with an independent set of size r{sup}n (but no guarantee for γ≤1/2). We also give an algorithm which finds an O(n{sup}0.2072)-coloring given a 3-colorable graph, improving upon the work of Arora, Chlamtac and Charikar. Our approach stands in contrast to a long series of inapproximability results in the Lovdsz Schrijver linear programming (LP) and SDP hierarchies for other problems.
机译:我们介绍了一种框架,用于基于近似算法的Lasserre层次结构来研究Semidefinite编程(SDP)放松,以便在组合问题的近似算法中。作为我们的方法的应用,我们为两个问题提供了改进的近似算法。我们表明,对于某些固定常数ε> 0,给定包含独立尺寸((1/2)-E)n的三均匀编程,我们可以找到独立的大小ω(n {sup}ε)。 。这改善了Krivelevich,Nathaniel和Sudakov的结果,该结果为具有独立尺寸R {sup}的超图,从而提供了一个算法的算法,用于查找独立的大小ω{top}〜(n {sup}(6r-3))的超图。 n(但没有保证γ≤1/ 2)。我们还给出了一种算法,该算法可以找到一个o(n {sup} 0.2072) - 给定3可色图,从而改善了arora,chlamtac和charikar的工作。我们的方法与LovdSz Schrijer线性编程(LP)和其他问题的SDP层次结构相比,这一方法与漫长的一系列差异结果相反。

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