The limits of SDP relaxations for general-valued CSPs
Abstract
It has been shown that for a general-valued constraint language the following statements are equivalent: (1) any instance of can be solved to optimality using a constant level of the Sherali-Adams LP hierarchy; (2) any instance of can be solved to optimality using the third level of the Sherali-Adams LP hierarchy; (3) the support of satisfies the "bounded width condition", i.e., it contains weak near-unanimity operations of all arities. We show that if the support of violates the bounded width condition then not only is not solved by a constant level of the Sherali-Adams LP hierarchy but it is also not solved by levels of the Lasserre SDP hierarchy (also known as the sum-of-squares SDP hierarchy). For corresponding to linear equations in an Abelian group, this result follows from existing work on inapproximability of Max-CSPs. By a breakthrough result of Lee, Raghavendra, and Steurer [STOC'15], our result implies that for any whose support violates the bounded width condition no SDP relaxation of polynomial-size solves . We establish our result by proving that various reductions preserve exact solvability by the Lasserre SDP hierarchy (up to a constant factor in the level of the hierarchy). Our results hold for general-valued constraint languages, i.e., sets of functions on a fixed finite domain that take on rational or infinite values, and thus also hold in notable special cases of -valued languages (CSPs), -valued languages (Min-CSPs/Max-CSPs), and -valued languages (finite-valued CSPs).
Keywords
Cite
@article{arxiv.1612.01147,
title = {The limits of SDP relaxations for general-valued CSPs},
author = {Johan Thapper and Stanislav Zivny},
journal= {arXiv preprint arXiv:1612.01147},
year = {2018}
}
Comments
Full version of a LICS'17 paper. Builds on and extends arXiv:1606.02577. arXiv admin note: text overlap with arXiv:1606.02577