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We study the connection between directed isoperimetric inequalities and monotonicity testing. In recent years, this connection has unlocked breakthroughs for testing monotonicity of functions defined on discrete domains. Inspired the rich…

Data Structures and Algorithms · Computer Science 2023-07-06 Renato Ferreira Pinto

In this paper, we study the query complexity of Boolean functions in the presence of uncertainty, motivated by parallel computation with an unlimited number of processors where inputs are allowed to be unknown. We allow each query to…

Computational Complexity · Computer Science 2025-07-02 Deepu Benson , Balagopal Komarath , Nikhil Mande , Sai Soumya Nalli , Jayalal Sarma , Karteek Sreenivasaiah

The well-known DeMillo-Lipton-Schwartz-Zippel lemma says that $n$-variate polynomials of total degree at most $d$ over grids, i.e. sets of the form $A_1 \times A_2 \times \cdots \times A_n$, form error-correcting codes (of distance at least…

Computational Complexity · Computer Science 2018-12-17 Mitali Bafna , Srikanth Srinivasan , Madhu Sudan

A Boolean function $f:\{0,1\}^n\to \{0,1\}$ is $k$-linear if it returns the sum (over the binary field $F_2$) of $k$ coordinates of the input. In this paper, we study property testing of the classes $k$-Linear, the class of all $k$-linear…

Computational Complexity · Computer Science 2020-06-09 Nader H. Bshouty

We investigate the computational efficiency of multitask learning of Boolean functions over the $d$-dimensional hypercube, that are related by means of a feature representation of size $k \ll d$ shared across all tasks. We present a…

Machine Learning · Computer Science 2022-09-08 Konstantina Bairaktari , Guy Blanc , Li-Yang Tan , Jonathan Ullman , Lydia Zakynthinou

We establish a generic form of hardness amplification for the approximability of constant-depth Boolean circuits by polynomials. Specifically, we show that if a Boolean circuit cannot be pointwise approximated by low-degree polynomials to…

Computational Complexity · Computer Science 2014-04-29 Mark Bun , Justin Thaler

Equivalence testing, a fundamental problem in the field of distribution testing, seeks to infer if two unknown distributions on $[n]$ are the same or far apart in the total variation distance. Conditional sampling has emerged as a powerful…

Data Structures and Algorithms · Computer Science 2024-03-08 Diptarka Chakraborty , Sourav Chakraborty , Gunjan Kumar , Kuldeep S. Meel

Consider the following Online Boolean Matrix-Vector Multiplication problem: We are given an $n\times n$ matrix $M$ and will receive $n$ column-vectors of size $n$, denoted by $v_1,\ldots,v_n$, one by one. After seeing each vector $v_i$, we…

Data Structures and Algorithms · Computer Science 2015-11-24 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai , Thatchaphol Saranurak

We prove that any non-adaptive algorithm that tests whether an unknown Boolean function $f: \{0, 1\}^n\to \{0, 1\}$ is a $k$-junta or $\epsilon$-far from every $k$-junta must make $\widetilde{\Omega}(k^{3/2} / \epsilon)$ many queries for a…

Computational Complexity · Computer Science 2017-04-24 Xi Chen , Rocco A. Servedio , Li-Yang Tan , Erik Waingarten , Jinyu Xie

The {\em Total Influence} ({\em Average Sensitivity) of a discrete function is one of its fundamental measures. We study the problem of approximating the total influence of a monotone Boolean function \ifnum\plusminus=1 $f: \{\pm1\}^n…

Data Structures and Algorithms · Computer Science 2011-01-28 Dana Ron , Ronitt Rubinfeld , Muli Safra , Omri Weinstein

The quantum query complexity of Boolean matrix multiplication is typically studied as a function of the matrix dimension, n, as well as the number of 1s in the output, \ell. We prove an upper bound of O (n\sqrt{\ell}) for all values of…

Quantum Physics · Physics 2014-12-17 Stacey Jeffery , Robin Kothari , Frédéric Magniez

We give the first agnostic, efficient, proper learning algorithm for monotone Boolean functions. Given $2^{\tilde{O}(\sqrt{n}/\varepsilon)}$ uniformly random examples of an unknown function $f:\{\pm 1\}^n \rightarrow \{\pm 1\}$, our…

Data Structures and Algorithms · Computer Science 2023-05-25 Jane Lange , Arsen Vasilyan

We establish new exponential in dimension lower bounds for the Maximum Halfspace Discrepancy problem, which models linear classification. Both are fundamental problems in computational geometry and machine learning in their exact and…

Computational Geometry · Computer Science 2026-03-20 Alexander Munteanu , Simon Omlor , Jeff M. Phillips

We study the extremal competitive ratio of Boolean function evaluation. We provide the first non-trivial lower and upper bounds for classes of Boolean functions which are not included in the class of monotone Boolean functions. For the…

Data Structures and Algorithms · Computer Science 2014-02-11 Ferdinando Cicalese , Travis Gagie , Eduardo Laber , Martin Milanic

Let $U_{k,N}$ denote the Boolean function which takes as input $k$ strings of $N$ bits each, representing $k$ numbers $a^{(1)},\dots,a^{(k)}$ in $\{0,1,\dots,2^{N}-1\}$, and outputs 1 if and only if $a^{(1)} + \cdots + a^{(k)} \geq 2^N.$…

Computational Complexity · Computer Science 2015-08-14 Xi Chen , Igor C. Oliveira , Rocco A. Servedio

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

Recent works explore deep learning's success by examining functions or data with hierarchical structure. To study the learning complexity of functions with hierarchical structure, we study the noise stability of functions with tree…

Probability · Mathematics 2025-09-30 Rupert Li , Elchanan Mossel

Let $[q] = \{0,1,\ldots,q-1\}$, let $\Delta[q]$ denote the simplex of probability measures on $[q]$, and let $\gamma$ denote the Lebesgue measure normalized on $\Delta[q]$. We prove that for any symmetric monotone function $f \colon[q]^n…

Probability · Mathematics 2026-05-20 Saba Lepsveridze , Allen Lin

Monotonicity is a key qualitative prediction of a wide array of economic models derived via robust comparative statics. It is therefore important to design effective and practical econometric methods for testing this prediction in empirical…

Statistics Theory · Mathematics 2019-07-10 Denis Chetverikov

We give a quantum algorithm for evaluating a class of boolean formulas (such as NAND trees and 3-majority trees) on a restricted set of inputs. Due to the structure of the allowed inputs, our algorithm can evaluate a depth $n$ tree using…

Quantum Physics · Physics 2012-07-04 Bohua Zhan , Shelby Kimmel , Avinatan Hassidim