Beyond Talagrand Functions: New Lower Bounds for Testing Monotonicity and Unateness
Computational Complexity
2017-08-22 v2
Abstract
We prove a lower bound of for the query complexity of any two-sided and adaptive algorithm that tests whether an unknown Boolean function is monotone or far from monotone. This improves the recent bound of for the same problem by Belovs and Blais [BB15]. Our result builds on a new family of random Boolean functions that can be viewed as a two-level extension of Talagrand's random DNFs. Beyond monotonicity, we also prove a lower bound of for any two-sided and adaptive algorithm, and a lower bound of for any one-sided and non-adaptive algorithm for testing unateness, a natural generalization of monotonicity. The latter matches the recent linear upper bounds by Khot and Shinkar [KS15] and by Chakrabarty and Seshadhri [CS16].
Keywords
Cite
@article{arxiv.1702.06997,
title = {Beyond Talagrand Functions: New Lower Bounds for Testing Monotonicity and Unateness},
author = {Xi Chen and Erik Waingarten and Jinyu Xie},
journal= {arXiv preprint arXiv:1702.06997},
year = {2017}
}