Quantcast

Testing Unateness of Real-Valued Functions

Research paper by Roksana Baleshzar, Meiram Murzabulatov, Ramesh Krishnan S. Pallavoor, Sofya Raskhodnikova

Indexed on: 26 Aug '16Published on: 26 Aug '16Published in: arXiv - Computer Science - Data Structures and Algorithms



Abstract

We give a unateness tester for functions of the form $f:[n]^d\rightarrow R$, where $n,d\in \mathbb{N}$ and $R\subseteq \mathbb{R}$ with query complexity $O(\frac{d\log (\max(d,n))}{\epsilon})$. Previously known unateness testers work only for Boolean functions over the domain $\{0,1\}^d$. We show that every unateness tester for real-valued functions over hypergrid has query complexity $\Omega(\min\{d, |R|^2\})$. Consequently, our tester is nearly optimal for real-valued functions over $\{0,1\}^d$. We also prove that every nonadaptive, 1-sided error unateness tester for Boolean functions needs $\Omega(\sqrt{d}/\epsilon)$ queries. Previously, no lower bounds for testing unateness were known.