English
Related papers

Related papers: Junta correlation is testable

200 papers

We study the problems of learning and testing junta distributions on $\{-1,1\}^n$ with respect to the uniform distribution, where a distribution $p$ is a $k$-junta if its probability mass function $p(x)$ depends on a subset of at most $k$…

Data Structures and Algorithms · Computer Science 2020-04-28 Xi Chen , Rajesh Jayaram , Amit Levi , Erik Waingarten

In this work, we consider the problems of learning junta distributions, their quantum counterparts (quantum junta states) and $\mathsf{QAC}^0$ circuits, which we show to be close to juntas. (1) Junta distributions. A probability…

Quantum Physics · Physics 2026-05-21 Jinge Bao , Francisco Escudero-Gutiérrez

We present an adaptive algorithm with one-sided error for the problem of junta testing for Boolean function under the challenging distribution-free setting, the query complexity of which is $\widetilde O(k)/\epsilon$. This improves the…

Computational Complexity · Computer Science 2023-01-27 Xiaojin Zhang

We introduce a new model for testing graph properties which we call the \emph{rejection sampling model}. We show that testing bipartiteness of $n$-nodes graphs using rejection sampling queries requires complexity $\widetilde{\Omega}(n^2)$.…

Computational Complexity · Computer Science 2018-05-04 Amit Levi , Erik Waingarten

A Boolean function f of n variables is said to be q-locally correctable if, given a black-box access to a function g which is "close" to an isomorphism f_sigma(x)=f_sigma(x_1, ..., x_n) = f(x_sigma(1), ..., x_sigma(n)) of f, we can compute…

Computational Complexity · Computer Science 2012-10-23 Noga Alon , Amit Weinstein

We show that for any constant $\epsilon > 0$ and $p \ge 1$, it is possible to distinguish functions $f : \{0,1\}^n \to [0,1]$ that are submodular from those that are $\epsilon$-far from every submodular function in $\ell_p$ distance with a…

Data Structures and Algorithms · Computer Science 2016-11-24 Eric Blais , Abhinav Bommireddi

We study the problem of learning junta distributions on $\{0, 1\}^n$, where a distribution is a $k$-junta if its probability mass function depends on a subset of at most $k$ variables. We make two main contributions: - We show that learning…

Machine Learning · Computer Science 2025-07-15 Lorenzo Beretta

We improve both upper and lower bounds for the distribution-free testing of monotone conjunctions. Given oracle access to an unknown Boolean function $f:\{0,1\}^n \rightarrow \{0,1\}$ and sampling oracle access to an unknown distribution…

Discrete Mathematics · Computer Science 2015-11-12 Xi Chen , Jinyu Xie

A Boolean function f over n variables is said to be q-locally correctable if, given a black-box access to a function g which is "close" to an isomorphism f_sigma of f, we can compute f_sigma(x) for any x in Z_2^n with good probability using…

Computational Complexity · Computer Science 2011-12-30 Noga Alon , Amit Weinstein

We study the question of local testability of low (constant) degree functions from a product domain $S_1 \times \dots \times {S}_n$ to a field $\mathbb{F}$, where ${S_i} \subseteq \mathbb{F}$ can be arbitrary constant sized sets. We show…

Computational Complexity · Computer Science 2024-11-12 Prashanth Amireddy , Srikanth Srinivasan , Madhu Sudan

We study the relative-error property testing model for Boolean functions that was recently introduced in the work of Chen et al. (SODA 2025). In relative-error testing, the testing algorithm gets uniform random satisfying assignments as…

Computational Complexity · Computer Science 2025-04-15 Xi Chen , William Pires , Toniann Pitassi , Rocco A. Servedio

We study the problem of learning k-juntas given access to examples drawn from a number of different product distributions. Thus we wish to learn a function f : {-1,1}^n -> {-1,1} that depends on k (unknown) coordinates. While the best known…

Machine Learning · Computer Science 2008-04-25 Jan Arpe , Elchanan Mossel

We take a different look at the problem of testing the independence of two metric-space-valued random variables using the distance correlation. Instead of testing if the distance correlation vanishes exactly, we are interested in the…

Statistics Theory · Mathematics 2025-11-19 Holger Dette , Marius Kroll

Numerous problems in extremal hypergraph theory ask to determine the maximal size of a $k$-uniform hypergraph on $n$ vertices that does not contain an `enlarged' copy $H^+$ of a fixed hypergraph $H$. These include well-known problems such…

Combinatorics · Mathematics 2021-08-12 Nathan Keller , Noam Lifshitz

In this paper, we study the following variant of the junta learning problem. We are given oracle access to a Boolean function $f$ on $n$ variables that only depends on $k$ variables, and, when restricted to them, equals some predefined…

Quantum Physics · Physics 2014-10-29 Aleksandrs Belovs

We revisit the problem of tolerant distribution testing. That is, given samples from an unknown distribution $p$ over $\{1, \dots, n\}$, is it $\varepsilon_1$-close to or $\varepsilon_2$-far from a reference distribution $q$ (in total…

Data Structures and Algorithms · Computer Science 2021-11-10 Clément L. Canonne , Ayush Jain , Gautam Kamath , Jerry Li

Given a Boolean function $f$ provided as a black-box with $n$ variables, this paper will propose a quantum algorithm for testing if a certain variable is junta or $\epsilon$-far from being junta. The proposed algorithm constructs another…

Quantum Physics · Physics 2018-01-22 Khaled El-Wazan , Ahmed Younes , S. B. Doma

Let $f:\{0,1\}^n \rightarrow \{0,1\}$ be a Boolean function. The certificate complexity $C(f)$ is a complexity measure that is quadratically tight for the zero-error randomized query complexity $R_0(f)$: $C(f) \leq R_0(f) \leq C(f)^2$. In…

Computational Complexity · Computer Science 2017-08-03 Dmitry Gavinsky , Rahul Jain , Hartmut Klauck , Srijita Kundu , Troy Lee , Miklos Santha , Swagato Sanyal , Jevgenijs Vihrovs

We prove tight bounds of Theta(k log k) queries for non-adaptively testing whether a function f:{0,1}^n -> {0,1} is a k-parity or far from any k-parity. The lower bound combines a recent method of Blais, Brody and Matulef [BBM11] to get…

Computational Complexity · Computer Science 2013-07-04 Harry Buhrman , David Garcia-Soriano , Arie Matsliah , Ronald de Wolf

We consider the $k$-Clustering problem, which is for a given multiset of $n$ vectors $X\subset \mathbb{Z}^d$ and a nonnegative number $D$, to decide whether $X$ can be partitioned into $k$ clusters $C_1, \dots, C_k$ such that the cost…

Data Structures and Algorithms · Computer Science 2019-02-25 Fedor V. Fomin , Petr A. Golovach , Kirill Simonov