Junta correlation is testable
Abstract: The problem of tolerant junta testing is a natural and challenging problem which asks if the property of a function having some specified correlation with a $k$-Junta is testable. In this paper we give an affirmative answer to this question: We show that given distance parameters $\frac{1}{2} >c_u>c_{\ell} \ge 0$, there is a tester which given oracle access to $f:{-1,1}n \rightarrow {-1,1}$, with query complexity $ 2k \cdot \mathsf{poly}(k,1/|c_u-c_{\ell}|)$ and distinguishes between the following cases: $\mathbf{1.}$ The distance of $f$ from any $k$-junta is at least $c_u$; $\mathbf{2.}$ There is a $k$-junta $g$ which has distance at most $c_\ell$ from $f$. This is the first non-trivial tester (i.e., query complexity is independent of $n$) which works for all $1/2 > c_u > c_\ell \ge 0$. The best previously known results by Blais \emph{et~ al.}, required $c_u \ge 16 c_\ell$. In fact, with the same query complexity, we accomplish the stronger goal of identifying the most correlated $k$-junta, up to permutations of the coordinates. We can further improve the query complexity to $\mathsf{poly}(k, 1/|c_u-c_{\ell}|)$ for the (weaker) task of distinguishing between the following cases: $\mathbf{1.}$ The distance of $f$ from any $k'$-junta is at least $c_u$. $\mathbf{2.}$ There is a $k$-junta $g$ which is at a distance at most $c_\ell$ from $f$. Here $k'=O(k2/|c_u-c_\ell|)$. Our main tools are Fourier analysis based algorithms that simulate oracle access to influential coordinates of functions.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.