The notion of recoverable value was advocated in work of Feige, Immorlica, Mirrokni and Nazerzadeh [Approx 2009] as a measure of quality for approximation algorithms. There this concept was applied to facility location problems. In the current work we apply a similar framework to the maximum independent set problem (MIS). We say that an approximation algorithm has recoverable value @math , if for every graph it recovers an independent set of size at least @math , where @math is the degree of vertex @math , and @math ranges over all independent sets in @math . Hence, in a sense, from every vertex @math in the maximum independent set the algorithm recovers a value of at least @math towards the solution. This quality measure is most effective in graphs in which the maximum independent set is composed of low degree vertices. It easily follows from known results that some simple algorithms for MIS ensure @math . We design a new randomized algorithm for MIS that ensures an expected recoverable value of at least @math . In addition, we show that approximating MIS in graphs with a given @math -coloring within a ratio larger than @math is unique games hard. This rules out a natural approach for obtaining @math .
Greedy. For MIS, iteratively picking a minimum degree vertex, adding it to an independent set @math and deleting the vertex and its neighbors from the graph is guaranteed to find an independent set of size at least @math @cite_3 @cite_8 . Halldorsson and Radhakrishnan @cite_4 showed that this greedy algorithm produces an independent set of size at least @math (where @math denotes the fraction of vertices in the maximum independent set). For MWIS, weighted greedy that iteratively picks a vertex @math with minimum @math is guaranteed to find an independent set of size at least @math @cite_5 .
@cite_5 @cite_4 @cite_3 @cite_8
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Theminimum-degree greedy algorithm, or Greedy for short, is a simple and well-studied method for finding independent sets in graphs. We show that it achieves a performance ratio of (Δ+2) 3 for approximating independent sets in graphs with degree bounded by Δ. The analysis yields a precise characterization of the size of the independent sets found by the algorithm as a function of the independence number, as well as a generalization of Turan's bound. We also analyze the algorithm when run in combination with a known preprocessing technique, and obtain an improved @math performance ratio on graphs with average degree @math , improving on the previous best @math of Hochbaum. Finally, we present an efficient parallel and distributed algorithm attaining the performance guarantees of Greedy. We study the inapproximability of Vertex Cover and Independent Set on degree @math graphs. We prove that: Vertex Cover is Unique Games-hard to approximate to within a factor @math . This exactly matches the algorithmic result of Halperin halperin02improved up to the @math term. Independent Set is Unique Games-hard to approximate to within a factor @math . This improves the @math Unique Games hardness result of Samorodnitsky and Trevisan samorodnitsky06gowers . Additionally, our result does not rely on the construction of a query efficient PCP as in samorodnitsky06gowers . We obtain improved algorithms for finding small vertex covers in bounded degree graphs and hypergraphs. We use semidefinite programming to relax the problems and introduce new rounding techniques for these relaxations. On graphs with maximum degree at most @math , the algorithm achieves a performance ratio of @math for large @math , which improves the previously known ratio of @math obtained by Halld orsson and Radhakrishnan. Using similar techniques, we also present improved approximations for the vertex cover problem in hypergraphs. For k-uniform hypergraphs with n vertices, we achieve a ratio of @math for large n, and for k-uniform hypergraphs with maximum degree at most @math the algorithm achieves a ratio of @math for large @math . These results considerably improve the previous best ratio of @math for bounded degree k-uniform hypergraphs, and @math for general k-uniform hypergraphs, both obtained by Krivelevich. Using similar techniques, we also obtain an approximation algorithm for the weighted independent set problem, matching a recent result of Halldorsson. The notion of recoverable value was advocated in the work of Feige, Immorlica, Mirrokni and Nazerzadeh (APPROX 2009) as a measure of quality for approximation algorithms. There, this concept was applied to facility location problems. In the current work we apply a similar framework to the maximum independent set problem (MIS). We say that an approximation algorithm has recoverable factor ρ, if for every graph it recovers an independent set of size at least where d(v) is the degree of vertex v, and I ranges over all independent sets in G. Hence, in a sense, from every vertex v in the maximum independent set the algorithm recovers a value of at least toward the solution. This quality measure is most effective in graphs in which the maximum independent set is composed of low degree vertices. A simple greedy algorithm achieves . We design a new randomized algorithm for MIS that ensures an expected recoverable factor of at least . In passing, we prove that approximating MIS in graphs with a given k-coloring within a ratio larger than 2 k is unique-games hard. This rules out an alternative approach for obtaining . © 2013 Wiley Periodicals, Inc. Random Struct. Alg., 46, 142–159, 2015