Approximation schemes via Sherali-Adams hierarchy for dense constraint satisfaction problems and assignment problems

Authors:
Yuichi Yoshida;Yuan Zhou
Affiliations:
National Institute of Informatics & Preferred Infrastructure, Inc., Tokyo, Japan;Carnegie Mellon University, Pittsburgh, PA, USA
Venue:
Proceedings of the 5th conference on Innovations in theoretical computer science
Year:
2014

Citing 18
Cited 0

A hierarchy of relaxation between the continuous and convex hull representations

SIAM Journal on Discrete Mathematics
MAX-CUT has a randomized approximation scheme in dense graphs

Random Structures & Algorithms
Proof verification and the hardness of approximation problems

Journal of the ACM (JACM)
Polynomial time approximation schemes for dense instances of NP -hard problems

Journal of Computer and System Sciences
A randomized approximation scheme for metric MAX-CUT

Journal of Computer and System Sciences
The regularity lemma and approximation schemes for dense problems

FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Random sampling and approximation of MAX-CSPs

Journal of Computer and System Sciences - STOC 2002
Approximation schemes for Metric Bisection and partitioning

SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Tensor decomposition and approximation schemes for constraint satisfaction problems

Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Tight integrality gaps for Lovasz-Schrijver LP relaxations of vertex cover and max cut

Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Linear programming relaxations of maxcut

SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Linear Level Lasserre Lower Bounds for Certain k-CSPs

FOCS '08 Proceedings of the 2008 49th Annual IEEE Symposium on Foundations of Computer Science
Integrality gaps for Sherali-Adams relaxations

Proceedings of the forty-first annual ACM symposium on Theory of computing
How to Round Any CSP

FOCS '09 Proceedings of the 2009 50th Annual IEEE Symposium on Foundations of Computer Science
An Efficient Sparse Regularity Concept

SIAM Journal on Discrete Mathematics
Rounding Semidefinite Programming Hierarchies via Global Correlation

FOCS '11 Proceedings of the 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science
Approximating CSPs with global cardinality constraints using SDP hierarchies

Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
On LP-based approximability for strict CSPs

Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms

Quantified Score

Hi-index	0.00

Visualization

Abstract

We consider approximation schemes for the maximum constraint satisfaction problems and the maximum assignment problems. Though they are NP-Hard in general, if the instance is "dense" or "locally dense", then they are known to have approximation schemes that run in polynomial time or quasi-polynomial time. In this paper, we give a unified method of showing these approximation schemes based on the Sherali-Adams linear programming relaxation hierarchy. We also use our linear programming-based framework to show new algorithmic results on the optimization version of the hypergraph isomorphism problem.