On sketching approximations for symmetric Boolean CSPs
Abstract
A Boolean maximum constraint satisfaction problem, Max-CSP(), is specified by a predicate . An -variable instance of Max-CSP() consists of a list of constraints, each of which applies to distinct literals drawn from the variables. For , Chou, Golovnev, and Velusamy [CGV20, FOCS 2020] obtained explicit ratios characterizing the -space streaming approximability of every predicate. For , Chou, Golovnev, Sudan, and Velusamy [CGSV21, arXiv:2102.12351] proved a general dichotomy theorem for -space sketching algorithms: For every , there exists such that for every , Max-CSP() is -approximable by an -space linear sketching algorithm, but -approximation sketching algorithms require space. In this work, we give closed-form expressions for the sketching approximation ratios of multiple families of symmetric Boolean functions. Letting , we show that for odd , AND, and for even , AND. We also resolve the ratio for the "at-least--'s" function for all even ; the "exactly--'s" function for odd ; and fifteen other functions. We stress here that for general , according to [CGSV21], closed-form expressions for need not have existed a priori. Separately, for all threshold functions, we give optimal "bias-based" approximation algorithms generalizing [CGV20] while simplifying [CGSV21]. Finally, we investigate the -space streaming lower bounds in [CGSV21], and show that they are incomplete for AND.
Cite
@article{arxiv.2112.06319,
title = {On sketching approximations for symmetric Boolean CSPs},
author = {Joanna Boyland and Michael Hwang and Tarun Prasad and Noah Singer and Santhoshini Velusamy},
journal= {arXiv preprint arXiv:2112.06319},
year = {2023}
}
Comments
27 pages; same results but significant changes in presentation