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We prove the "Most informative boolean function" conjecture of Courtade and Kumar for high noise $\epsilon \ge 1/2 - \delta$, for some absolute constant $\delta > 0$. Namely, if $X$ is uniformly distributed in $\{0,1\}^n$ and $Y$ is…

Information Theory · Computer Science 2015-11-29 Alex Samorodnitsky

We introduce a simply stated conjecture regarding the maximum mutual information a Boolean function can reveal about noisy inputs. Specifically, let $X^n$ be i.i.d. Bernoulli(1/2), and let $Y^n$ be the result of passing $X^n$ through a…

Information Theory · Computer Science 2013-07-16 Gowtham R. Kumar , Thomas A. Courtade

Suppose $X$ is a uniformly distributed $n$-dimensional binary vector and $Y$ is obtained by passing $X$ through a binary symmetric channel with crossover probability $\alpha$. A recent conjecture by Courtade and Kumar postulates that…

Information Theory · Computer Science 2015-06-02 Or Ordentlich , Ofer Shayevitz , Omri Weinstein

We prove the Courtade-Kumar conjecture, for several classes of n-dimensional Boolean functions, for all $n \geq 2$ and for all values of the error probability of the binary symmetric channel, $0 \leq p \leq 1/2$. This conjecture states that…

Information Theory · Computer Science 2017-02-09 Septimia Sarbu

Suppose $\XX{N}$ is a uniformly distributed $N$-dimensional binary vector and $\YY{N}$ is obtained by passing $\XX{N}$ through a binary symmetric channel with crossover probability $\alpha$. Recently, Courtade and Kumar postulates that…

Information Theory · Computer Science 2017-10-20 Mustafa Kesal

We prove the Courtade-Kumar conjecture, which states that the mutual information between any Boolean function of an $n$-dimensional vector of independent and identically distributed inputs to a memoryless binary symmetric channel and the…

Information Theory · Computer Science 2017-01-17 Septimia Sarbu

This paper develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an…

Artificial Intelligence · Computer Science 2015-06-30 Wolfgang Gatterbauer , Dan Suciu

We prove the Courtade-Kumar conjecture, for certain classes of $n$-dimensional Boolean functions, $\forall n\geq 2$ and for all values of the error probability of the binary symmetric channel, $\forall 0 \leq p \leq \frac{1}{2}$. Let…

Information Theory · Computer Science 2017-02-15 Septimia Sarbu

In this work, we consider the problem of bounding the values of a covariance function corresponding to a continuous-time stationary stochastic process or signal. Specifically, for two signals whose covariance functions agree on a finite…

Signal Processing · Electrical Eng. & Systems 2021-10-07 Filip Elvander , Johan Karlsson , Toon van Waterschoot

This paper investigates the learnability of the nonlinearity property of Boolean functions using neural networks. We train encoder style deep neural networks to learn to predict the nonlinearity of Boolean functions from examples of…

Machine Learning · Computer Science 2025-02-04 Sriram Ranga , Nandish Chattopadhyay , Anupam Chattopadhyay

Monotone Boolean functions are a structurally important class of Boolean functions, but their restricted form imposes strong limitations on achievable nonlinearity. In this paper, we investigate whether evolutionary computation can evolve…

Neural and Evolutionary Computing · Computer Science 2026-04-21 Claude Carlet , Marko Čupić , Marko Ðurasevic , Domagoj Jakobovic , Luca Mariot , Stjepan Picek

Boolean functions are mathematical objects used in diverse applications. Different applications also have different requirements, making the research on Boolean functions very active. In the last 30 years, evolutionary algorithms have been…

Neural and Evolutionary Computing · Computer Science 2024-02-16 Claude Carlet , Marko Ðurasevic , Domagoj Jakobovic , Stjepan Picek , Luca Mariot

Building on the recently introduced notion of Boolean entropy, we define the corresponding Boolean Fisher information via a de Bruijn identity. We study the monotonicity of this Fisher information in the Boolean Central Limit Theorem and…

Probability · Mathematics 2026-03-02 Guillaume Cébron , Kewei Pan

A linear inference is a valid inequality of Boolean algebra in which each variable occurs at most once on each side. In this work we leverage recently developed graphical representations of linear formulae to build an implementation that is…

Logic in Computer Science · Computer Science 2024-02-14 Anupam Das , Alex Rice

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

This work presents a study of perturbations of symmetric Boolean functions. In particular, it establishes a connection between exponential sums of these perturbations and Diophantine equations of the form $$ \sum_{l=0}^n \binom{n}{l}…

Combinatorics · Mathematics 2018-01-12 Francis N. Castro , Oscar E. González , Luis A. Medina

We prove two conjectures on correlation inequalities for functions that are linear combinations of unimodal Boolean monotone nondecreasing functions

Combinatorics · Mathematics 2014-08-29 Vladimir Blinovsky

Let $X^n$ be a uniformly distributed $n$-dimensional binary vector, and $Y^n$ be the result of passing $X^n$ through a binary symmetric channel (BSC) with crossover probability $\alpha$. A recent conjecture postulated by Courtade and Kumar…

Information Theory · Computer Science 2019-07-18 Hengjie Yang , Richard D. Wesel

Determining functionals are tools to describe the finite dimensional long-term dynamics of infinite dimensional dynamical systems. There also exist several applications to infinite dimensional {\em random} dynamical systems. In these…

Chaotic Dynamics · Physics 2007-05-23 Igor Chueshov , Jinqiao Duan , Bjorn Schmalfuss

This paper presents a method to detect and recognize symmetries in Boolean functions. The idea is to use information theoretic measures of Boolean functions to detect sub-space of possible symmetric variables. Coupled with the new…

Other Computer Science · Computer Science 2007-10-15 Denis V. Popel
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