pith. sign in

arxiv: 1801.02816 · v1 · pith:S555CUREnew · submitted 2018-01-09 · 💻 cs.DS · cs.CC· cs.DM

Adaptive Boolean Monotonicity Testing in Total Influence Time

classification 💻 cs.DS cs.CCcs.DM
keywords testervarepsilonadaptivebooleaninfluencemonotonicitytestingtime
0
0 comments X
read the original abstract

The problem of testing monotonicity of a Boolean function $f:\{0,1\}^n \to \{0,1\}$ has received much attention recently. Denoting the proximity parameter by $\varepsilon$, the best tester is the non-adaptive $\widetilde{O}(\sqrt{n}/\varepsilon^2)$ tester of Khot-Minzer-Safra (FOCS 2015). Let $I(f)$ denote the total influence of $f$. We give an adaptive tester whose running time is $I(f)poly(\varepsilon^{-1}\log n)$.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.