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We study the problem of estimating a monotone function $f:\{0,1\}^d\to[0,1]$ from noisy observations at uniformly random vertices of the Boolean hypercube. As a measure of complexity for the target~$f$, we use the total $L^1$-influence…

Statistics Theory · Mathematics 2026-05-20 Gérard Biau

We study the probability of Boolean functions with small max influence to become constant under random restrictions. Let $f$ be a Boolean function such that the variance of $f$ is $\Omega(1)$ and all its individual influences are bounded by…

Computational Complexity · Computer Science 2022-08-19 Ronen Eldan , Avi Wigderson , Pei Wu

The influence of the $k$'th coordinate on a Boolean function $f:\{0,1\}^n \rightarrow \{0,1\}$ is the probability that flipping $x_k$ changes the value $f(x)$. The total influence $I(f)$ is the sum of influences of the coordinates. The…

Combinatorics · Mathematics 2018-06-06 Nathan Keller , Noam Lifshitz

The Ratios Conjecture of Conrey, Farmer and Zirnbauer predicts the answers to numerous questions in number theory, ranging from n-level densities and correlations to mollifiers to moments and vanishing at the central point. The conjecture…

Number Theory · Mathematics 2010-11-16 John Goes , Steven Jackson , Steven J. Miller , David Montague , Kesinee Ninsuwan , Ryan Peckner , Thuy Pham

We investigate random Bernoulli convolutions, namely, probability measures given by the infinite convolution \[ \mu_\omega = \mathop{\circledast}_{k=1}^{\infty} \left( \frac{\delta_0 + \delta_{\lambda_1 \lambda_2 \ldots \lambda_{k-1}…

Dynamical Systems · Mathematics 2025-08-06 Simon Baker , Henna Koivusalo , Sascha Troscheit , Xintian Zhang

Let $0 < \epsilon < 1/2$ be a noise parameter, and let $T_{\epsilon}$ be the noise operator acting on functions on the boolean cube $\{0,1\}^n$. Let $f$ be a nonnegative function on $\{0,1\}^n$. We upper bound the entropy of $T_{\epsilon}…

Information Theory · Computer Science 2016-06-23 Alex Samorodnitsky

We study two conjectures posed in the analysis of Boolean functions $f : \{-1, 1\}^n \to \{-1, 1\}$, in both of which, the Majority function plays a central role: the "Majority is Least Stable" (Benjamini et al., 1999) and the…

Computational Complexity · Computer Science 2026-04-09 Pritish Kamath , Ravi Kumar , Pasin Manurangsi

A Boolean function $f:\{0,1\}^n \to \{0,1\}$ is said to be noise sensitive if inserting a small random error in its argument makes the value of the function almost unpredictable. Benjamini, Kalai and Schramm showed that if the sum of…

Combinatorics · Mathematics 2010-03-10 Nathan Keller , Guy Kindler

We develop a new technique for proving concentration inequalities which relate between the variance and influences of Boolean functions. Using this technique, we 1. Settle a conjecture of Talagrand [Tal97] proving that $$\int_{\left\{…

Probability · Mathematics 2020-03-13 Ronen Eldan , Renan Gross

Consider a monotone Boolean function $f:\{0,1\}^n\to\{0,1\}$ and the canonical monotone coupling $\{\eta_p:p\in[0,1]\}$ of an element in $\{0,1\}^n$ chosen according to product measure with intensity $p\in[0,1]$. The random point…

Probability · Mathematics 2018-10-08 Daniel Ahlberg , Jeffrey E. Steif , Gábor Pete

We introduce a new notion of influence for symmetric convex sets over Gaussian space, which we term "convex influence". We show that this new notion of influence shares many of the familiar properties of influences of variables for monotone…

Computational Complexity · Computer Science 2021-09-08 Anindya De , Shivam Nadimpalli , Rocco A. Servedio

Let f:{-1,1}^n -> R be a real function on the hypercube, given by its discrete Fourier expansion, or, equivalently, represented as a multilinear polynomial. We say that it is Boolean if its image is in {-1,1}. We show that every function on…

Discrete Mathematics · Computer Science 2013-11-13 Tom Gur , Omer Tamuz

We show that on every product probability space, Boolean functions with small total influences are essentially the ones that are almost measurable with respect to certain natural sub-sigma algebras. This theorem in particular describes the…

Combinatorics · Mathematics 2011-11-15 Hamed Hatami

We study whether a uniformly random Boolean function $f : \{-1,1\}^p \to \{-1,1\}$ is determined by its Walsh--Fourier coefficients of degree at most $d$. We show that the threshold lies at $p/2$ up to an $O(\sqrt{p \log p})$ window: if \[…

Probability · Mathematics 2026-04-16 Yiming Chen

About twenty years ago we wrote a paper, "Boolean Functions whose Fourier Transform is Concentrated on the First Two Levels", \cite{FKN}. In it we offered several proofs of the statement that Boolean functions $f(x_1,x_2,\dots,x_n)$, whose…

Combinatorics · Mathematics 2021-05-10 Ehud Friedgut , GIl Kalai , Assaf Naor

We investigate ergodic-theoretical quantities and large deviation properties of one-dimensional intermittent maps, that have not only an indifferent fixed point but also a singular structure such that the uniform measure is invariant under…

Chaotic Dynamics · Physics 2015-06-18 Soya Shinkai , Yoji Aizawa

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

In this paper we study functions with low influences on product probability spaces. The analysis of boolean functions with low influences has become a central problem in discrete Fourier analysis. It is motivated by fundamental questions…

Probability · Mathematics 2007-05-23 Elchanan Mossel , Ryan O'Donnell , Krzysztof Oleszkiewicz

The seminal result of Kahn, Kalai and Linial shows that a coalition of $O(\frac{n}{\log n})$ players can bias the outcome of any Boolean function $\{0,1\}^n \to \{0,1\}$ with respect to the uniform measure. We extend their result to…

Discrete Mathematics · Computer Science 2019-02-21 Yuval Filmus , Lianna Hambardzumyan , Hamed Hatami , Pooya Hatami , David Zuckerman

A number of recent works have sought to generalize the Kolmogorov-Sinai entropy of probability-preserving transformations to the setting of Markov operators acting on the integrable functions on a probability space $(X,\mu)$. These have…

Dynamical Systems · Mathematics 2015-08-25 Tim Austin