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An efficient sparse regularity concept
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
An Efficient Sparse Regularity Concept
SIAM Journal on Discrete Mathematics
Approximation algorithms for semi-random partitioning problems
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Maximum cliques in graphs with small intersection number and random intersection graphs
MFCS'12 Proceedings of the 37th international conference on Mathematical Foundations of Computer Science
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Proceedings of the 4th conference on Innovations in Theoretical Computer Science
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The minimum bisection problem is to partition the vertices of a graph into two classes of equal size so as to minimize the number of crossing edges. Computing a minimum bisection is NP-hard in the worst case. In this paper we study a spectral heuristic for bisecting random graphs Gn(p,p′) with a planted bisection obtained as follows: partition n vertices into two classes of equal size randomly, and then insert edges inside the two classes with probability p′ and edges crossing the partition with probability p independently. If $n(p'-p)\geq c_0\sqrt{np'\ln(np')}$, where c0 is a suitable constant, then with probability 1 - o(1) the heuristic finds a minimum bisection of Gn(p,p′) along with a certificate of optimality. Furthermore, we show that the structure of the set of all minimum bisections of Gn(p,p′) undergoes a phase transition as $n(p'-p)=\Theta(\sqrt{np'\ln n})$. The spectral heuristic solves instances in the subcritical, the critical, and the supercritical phases of the phase transition optimally with probability 1 - o(1). These results extend previous work of Boppana [Proc. 28th FOCS (1987) 280–285]. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2006An extended abstract version of this paper appeared in Proc. 16th SODA (2005), pp. 850–859.