Approximating Rectangles by Juntas and Weakly-Exponential Lower Bounds for LP Relaxations of CSPs

30 Dec 2017 Kothari Pravesh K. Meka Raghu Raghavendra Prasad

We show that for constraint satisfaction problems (CSPs), sub-exponential size linear programming relaxations are as powerful as $n^{\Omega(1)}$-rounds of the Sherali-Adams linear programming hierarchy. As a corollary, we obtain sub-exponential size lower bounds for linear programming relaxations that beat random guessing for many CSPs such as MAX-CUT and MAX-3SAT... (read more)

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  • COMPUTATIONAL COMPLEXITY
  • DISCRETE MATHEMATICS
  • DATA STRUCTURES AND ALGORITHMS
  • COMBINATORICS