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  • Titel: Global Cardinality Constraints Make Approximating Some Max-2-CSPs Harder
  • Beteiligte: Austrin, Per [Verfasser:in]; Stanković, Aleksa [Verfasser:in]
  • Erschienen: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2019
  • Sprache: Englisch
  • DOI: https://doi.org/10.4230/LIPIcs.APPROX-RANDOM.2019.24
  • Schlagwörter: inapproximability ; Max-Cut ; global cardinality constraints ; Max-2-Sat ; semidefinite programming ; Constraint satisfaction problems ; Unique Games Conjecture
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  • Beschreibung: Assuming the Unique Games Conjecture, we show that existing approximation algorithms for some Boolean Max-2-CSPs with cardinality constraints are optimal. In particular, we prove that Max-Cut with cardinality constraints is UG-hard to approximate within ~0.858, and that Max-2-Sat with cardinality constraints is UG-hard to approximate within ~0.929. In both cases, the previous best hardness results were the same as the hardness of the corresponding unconstrained Max-2-CSP (~0.878 for Max-Cut, and ~0.940 for Max-2-Sat). The hardness for Max-2-Sat applies to monotone Max-2-Sat instances, meaning that we also obtain tight inapproximability for the Max-k-Vertex-Cover problem.
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