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  • Titel: Matroid-Constrained Maximum Vertex Cover: Approximate Kernels and Streaming Algorithms
  • Beteiligte: Huang, Chien-Chung [VerfasserIn]; Sellier, François [VerfasserIn]
  • Erschienen: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2022
  • Sprache: Englisch
  • DOI: https://doi.org/10.4230/LIPIcs.SWAT.2022.27
  • Schlagwörter: Maximum vertex cover ; streaming ; matroid ; approximate kernel
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  • Beschreibung: Given a graph with weights on the edges and a matroid imposed on the vertices, our problem is to choose a subset of vertices that is independent in the matroid, with the objective of maximizing the total weight of covered edges. This problem is a generalization of the much studied max k-vertex cover problem, where the matroid is the simple uniform matroid, and it is also a special case of maximizing a monotone submodular function under a matroid constraint. In this work, we give a Fixed Parameter Tractable Approximation Scheme (FPT-AS) when the given matroid is a partition matroid, a laminar matroid, or a transversal matroid. Precisely, if k is the rank of the matroid, we obtain (1 - ε) approximation using (1/(ε))^{O(k)}n^{O(1)} time for partition and laminar matroids and using (1/(ε)+k)^{O(k)}n^{O(1)} time for transversal matroids. This extends a result of Manurangsi for uniform matroids [Pasin Manurangsi, 2018]. We also show that these ideas can be applied in the context of (single-pass) streaming algorithms. Our FPT-AS introduces a new technique based on matroid union, which may be of independent interest in extremal combinatorics.
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