Satisfiability of Ordering CSPs Above Average

March 12, 2015 Β· Declared Dead Β· πŸ› IEEE Annual Symposium on Foundations of Computer Science

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Authors Konstantin Makarychev, Yury Makarychev, Yuan Zhou arXiv ID 1503.03851 Category cs.DS: Data Structures & Algorithms Citations 3 Venue IEEE Annual Symposium on Foundations of Computer Science Last Checked 4 months ago
Abstract
We study the satisfiability of ordering constraint satisfaction problems (CSPs) above average. We prove the conjecture of Gutin, van Iersel, Mnich, and Yeo that the satisfiability above average of ordering CSPs of arity $k$ is fixed-parameter tractable for every $k$. Previously, this was only known for $k=2$ and $k=3$. We also generalize this result to more general classes of CSPs, including CSPs with predicates defined by linear inequalities. To obtain our results, we prove a new Bonami-type inequality for the Efron-Stein decomposition. The inequality applies to functions defined on arbitrary product probability spaces. In contrast to other variants of the Bonami Inequality, it does not depend on the mass of the smallest atom in the probability space. We believe that this inequality is of independent interest.
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