Randomized rounding: a technique for provably good algorithms and algorithmic proofs
Combinatorica - Theory of Computing
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SIAM Journal on Discrete Mathematics
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Journal of the ACM (JACM)
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
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SIAM Journal on Discrete Mathematics
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Journal of the ACM (JACM)
Constructing Worst Case Instances for Semidefinite Programming Based Approximation Algorithms
SIAM Journal on Discrete Mathematics
Improved approximation of max-cut on graphs of bounded degree
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On the optimality of the random hyperplane rounding technique for max cut
Random Structures & Algorithms - Probabilistic methods in combinatorial optimization
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An optimal sdp algorithm for max-cut, and equally optimal long code tests
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Approximation Algorithms for Max 3-Section Using Complex Semidefinite Programming Relaxation
COCOA '09 Proceedings of the 3rd International Conference on Combinatorial Optimization and Applications
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Mathematics of Operations Research
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SIAM Journal on Computing
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Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Journal of Combinatorial Theory Series B
Journal of Combinatorial Optimization
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Several combinatorial optimization problems can be approximated using algorithms based on semidefinite programming. In many of these algorithms a semidefinite relaxation of the underlying problem is solved yielding an optimal vector configuration v1,...,vn. This vector configuration is then rounded into a {0, 1} solution. We present a procedure called RPR2 (Random Projection followed by Randomized Rounding) for rounding the solution of such semidefinite programs. We show that the random hyperplane rounding technique introduced by Goemans and Williamson, and its variant that involves outward rotation, are both special cases of RPR2. We illustrate the use of RPR2 by presenting two applications. For Max-Bisection we improve the approximation ratio. For Max-Cut, we improve the tradeoff curve (presented by Zwick) that relates the approximation ratio to the size of the maximum cut in a graph.