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Related papers: A new bound for the Fourier-Entropy-Influence conj…

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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

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

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

In this paper, we prove that most of the boolean functions, $f : \{-1,1\}^n \rightarrow \{-1,1\}$ satisfy the Fourier Entropy Influence (FEI) Conjecture due to Friedgut and Kalai (Proc. AMS'96). The conjecture says that the Entropy of a…

Combinatorics · Mathematics 2011-10-21 Bireswar Das , Manjish Pal , Vijay Visavaliya

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 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

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

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

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

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

A function defined on the Boolean hypercube is $k$-Fourier-sparse if it has at most $k$ nonzero Fourier coefficients. For a function $f: \mathbb{F}_2^n \rightarrow \mathbb{R}$ and parameters $k$ and $d$, we prove a strong upper bound on the…

Data Structures and Algorithms · Computer Science 2015-04-08 Ishay Haviv , Oded Regev

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

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 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

The Riemann-Lebesque Theorem is commonly proved in a few strokes using the theory of Lebesque integration. Here, the upper bound $2\pi|c_k(f)|\le S_k(f)-s_k(f)$ for the Fourier coefficients $c_k$ is proved in terms of majoring and minoring…

funct-an · Mathematics 2008-02-03 Maurice H. P. M. van Putten

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 that the Fourier dimension of any Boolean function with Fourier sparsity $s$ is at most $O\left(s^{2/3}\right)$. Our proof method yields an improved bound of $\widetilde{O}(\sqrt{s})$ assuming a conjecture of…

Computational Complexity · Computer Science 2014-07-15 Swagato Sanyal

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

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

For a function $f$ over the discrete cube, the total $L_1$ influence of $f$ is defined as $\sum_{i=1}^n \|\partial_i f\|_1$, where $\partial_i f$ denotes the discrete derivative of $f$ in the direction $i$. In this work, we show that the…

Computational Complexity · Computer Science 2014-04-15 Artūrs Bačkurs , Mohammad Bavarian
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