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Related papers: The Entropy Influence Conjecture Revisited

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The Fourier Entropy-Influence (FEI) Conjecture of Friedgut and Kalai states that ${\bf H}[f] \leq C \cdot {\bf I}[f]$ holds for every Boolean function $f$, where ${\bf H}[f]$ denotes the spectral entropy of $f$, ${\bf I}[f]$ is its total…

Computational Complexity · Computer Science 2019-01-25 Guy Shalev

The Fourier-Entropy Influence (FEI) Conjecture states that for any Boolean function $f:\{+1,-1\}^n \to \{+1,-1\}$, the Fourier entropy of $f$ is at most its influence up to a universal constant factor. While the FEI conjecture has been…

Computational Complexity · Computer Science 2019-03-29 Sourav Chakraborty , Sushrut Karmalkar , Srijita Kundu , Satyanarayana V. Lokam , Nitin Saurabh

The Fourier Entropy-Influence (FEI) conjecture of Friedgut and Kalai [FK96] seeks to relate two fundamental measures of Boolean function complexity: it states that $H[f] \leq C Inf[f]$ holds for every Boolean function $f$, where $H[f]$…

Computational Complexity · Computer Science 2013-04-05 Ryan O'Donnell , Li-Yang Tan

The total influence of a function is a central notion in analysis of Boolean functions, and characterizing functions that have small total influence is one of the most fundamental questions associated with it. The KKL theorem and the…

Discrete Mathematics · Computer Science 2020-05-08 Esty Kelman , Guy Kindler , Noam Lifshitz , Dor Minzer , Muli Safra

Given $f:\{-1, 1\}^n \rightarrow \{-1, 1\}$, define the \emph{spectral distribution} of $f$ to be the distribution on subsets of $[n]$ in which the set $S$ is sampled with probability $\widehat{f}(S)^2$. Then the Fourier Entropy-Influence…

Computational Complexity · Computer Science 2013-12-12 Andrew Wan , John Wright , Chenggang Wu

Given a Boolean function $f:\{-1,1\}^n\to \{-1,1\}$, the Fourier distribution assigns probability $\widehat{f}(S)^2$ to $S\subseteq [n]$. The Fourier Entropy-Influence (FEI) conjecture of Friedgut and Kalai asks if there exist a universal…

Computational Complexity · Computer Science 2021-09-20 Srinivasan Arunachalam , Sourav Chakraborty , Michal Koucký , Nitin Saurabh , Ronald de Wolf

The entropy/influence conjecture, raised by Friedgut and Kalai in 1996, seeks to relate two different measures of concentration of the Fourier coefficients of a Boolean function. Roughly saying, it claims that if the Fourier spectrum is…

Combinatorics · Mathematics 2011-05-16 Nathan Keller , Elchanan Mossel , Tomer Schlank

Every Boolean function can be uniquely represented as a multilinear polynomial. The entropy and the total influence are two ways to measure the concentration of its Fourier coefficients, namely the monomial coefficients in this…

Computational Complexity · Computer Science 2017-11-03 Rani Hod

This manuscript includes some classical results we select apart from the new results we've found on the Analysis of Boolean Functions and Fourier-Entropy-Influence conjecture. We try to ensure the self-completeness of this work so that…

Combinatorics · Mathematics 2023-11-21 Xiao Han

In this paper, we prove that the Fourier entropy of an $n$-dimensional boolean function $f$ can be upper-bounded by $O(I(f)+ \sum\limits_{k\in[n]}I_k(f)\log \frac{1}{I_k(f)})$, where $I(f)$ is its total influence and $I_k(f)$ is the…

Combinatorics · Mathematics 2025-12-11 Xiao Han

We describe a new construction of Boolean functions. A specific instance of our construction provides a 30-variable Boolean function having min-entropy/influence ratio to be $128/45 \approx 2.8444$ which is presently the highest known value…

Computational Complexity · Computer Science 2024-01-19 Aniruddha Biswas , Palash Sarkar

We consider Boolean functions f:{-1,1}^n->{-1,1} that are close to a sum of independent functions on mutually exclusive subsets of the variables. We prove that any such function is close to just a single function on a single subset. We also…

Probability · Mathematics 2015-12-31 Aviad Rubinstein , Muli Safra

We prove that for any decision tree calculating a boolean function $f:\{-1,1\}^n\to\{-1,1\}$, \[ \Var[f] \le \sum_{i=1}^n \delta_i \Inf_i(f), \] where $\delta_i$ is the probability that the $i$th input variable is read and $\Inf_i(f)$ is…

Computational Complexity · Computer Science 2007-05-23 Ryan O'Donnell , Michael Saks , Oded Schramm , Rocco A. Servedio

We study Boolean functions on the $p$-biased hypercube $(\{0,1\}^n,\mu_p^n)$ through the lens of Fourier (spectral) entropy, i.e. the Shannon entropy of the squared $p$-biased Fourier coefficients. Motivated by recent restriction-based…

Combinatorics · Mathematics 2026-03-13 Fan Chang

We strengthen Han's Fourier entropy-influence inequality $$ H[\widehat{f}] \leq C_{1}I(f) + C_{2}\sum_{i\in [n]}I_{i}(f)\ln\frac{1}{I_{i}(f)} $$ originally proved for $\{-1,1\}$-valued Boolean functions with $C_{1}=3+2\ln 2$ and $C_{2}=1$.…

Information Theory · Computer Science 2025-12-10 Peijie Li , Guangyue Han

In this expository article, we study the relation between the boolean functions and the hypercontractivity theorems of Aline Bonami. We focus on the social choice theory, and present some of the most important results in the area, such as…

Classical Analysis and ODEs · Mathematics 2025-02-20 María José González , Paul MacManus , María Cristina Pereyra

Chang's lemma (Duke Mathematical Journal, 2002) is a classical result with applications across several areas in mathematics and computer science. For a Boolean function $f$ that takes values in {-1,1} let $r(f)$ denote its Fourier rank. For…

Computational Complexity · Computer Science 2021-05-25 Sourav Chakraborty , Nikhil S. Mande , Rajat Mittal , Tulasimohan Molli , Manaswi Paraashar , Swagato Sanyal

A celebrated theorem of Friedgut says that every function $f:\{0,1\}^n \to \{0,1\}$ can be approximated by a function $g:\{0,1\}^n \to \{0,1\}$ with $\|f-g\|_2^2 \le \epsilon$ which depends only on $e^{O(I_f/\epsilon)}$ variables where…

Probability · Mathematics 2009-03-14 Hamed Hatami

Consider a Boolean function f on the n-dimensional hypercube, and a set of variables (indexed by) $S \subset \{1,2,\ldots,n\}.$ The coalition influence of the variables S on a function f is the probability that after a random assignment of…

Combinatorics · Mathematics 2026-01-19 Tomasz Przybyłowski

We present a regularity lemma for Boolean functions $f:\{-1,1\}^n \to \{-1,1\}$ based on noisy influence, a measure of how locally correlated $f$ is with each input bit. We provide an application of the regularity lemma to weaken the…

Computational Complexity · Computer Science 2016-10-25 Chris Jones
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