Approximating the independence number and the chromatic number in expected polynomial time

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Abstract

The independence number of a graph and its chromatic number are hard to approximate. It is known that, unless coRP = NP, there is no polynomial time algorithm which approximates any of these quantities within a factor of n1−ε for graphs on n vertices. We show that the situation is significantly better for the average case. For every edge probability p = p(n) in the range n−1/2+ε ≤ p ≤ 3/4, we present an approximation algorithm for the independence number of graphs on n vertices, whose approximation ratio is O((np)1/2/ log n) and whose expected running time over the probability space G(n,p) is polynomial. An algorithm with similar features is described also for the chromatic number. A key ingredient in the analysis of both algorithms is a new large deviation inequality for eigenvalues of random matrices, obtained through an application of Talagrand’s inequality.

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Krivelevich, M., & Vu, V. H. (2000). Approximating the independence number and the chromatic number in expected polynomial time. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1853, pp. 13–24). Springer Verlag. https://doi.org/10.1007/3-540-45022-x_3

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