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Mutual information $I(X;Y)$ is a useful definition in information theory to estimate how much information the random variable $Y$ holds about the random variable $X$. One way to define the mutual information is by comparing the joint…

Information Theory · Computer Science 2022-04-14 Bulut Kuskonmaz , Jaron Skovsted Gundersen , Rafal Wisniewski

This paper considers derivation of $f$-divergence inequalities via the approach of functional domination. Bounds on an $f$-divergence based on one or several other $f$-divergences are introduced, dealing with pairs of probability measures…

Information Theory · Computer Science 2016-10-31 Igal Sason , Sergio Verdú

We prove that a balanced Boolean function on $S_{n}$ whose Fourier transform is highly concentrated on the first two irreducible representations of $S_{n}$, is close in structure to a dictatorship, a function which is determined by the…

Combinatorics · Mathematics 2017-07-03 David Ellis , Yuval Filmus , Ehud Friedgut

We show that many theorems which assert that two kinds of partitions of the same integer $n$ are equinumerous are actually special cases of a much stronger form of equality. We show that in fact there correspond partition statistics $X$ and…

Combinatorics · Mathematics 2007-05-23 Herbert S. Wilf

The main aim of this paper is to study the functional inequality \begin{equation*} \int_{[0,1]}f\bigl((1-t)x+ty\bigr)d\mu(t)\geq 0, \qquad x,y\in I \mbox{ with } x<y, \end{equation*} for a continuous unknown function $f:I\to{\mathbb R}$,…

Classical Analysis and ODEs · Mathematics 2025-03-28 Zsolt Páles , Tomasz Szostok

One of the most fundamental questions one can ask about a pair of random variables X and Y is the value of their mutual information. Unfortunately, this task is often stymied by the extremely large dimension of the variables. We might hope…

Statistical Mechanics · Physics 2017-06-21 Ryan G. James , John R. Mahoney , James P. Crutchfield

In this short note, we introduce probabilistic Cauchy functional equations, specifically, functional equations of the following form: $$ f(X_1 + X_2) \stackrel{d}{=} f(X_1) + f(X_2), $$ where $X_1$ and $X_2$ represent two independent…

Probability · Mathematics 2024-06-05 Ehsan Azmoodeh , Noah Beelders , Yuliya Mishura

We prove that any random variable $X$ whose moment generating function is point-wise upper bounded by that of $ G \sim \mathcal{N}(0,1) $ must be dominated by $ G/\mathbb{E}[|G|] $ in convex order, meaning $ \mathbb{E}[f(X)] \le…

Probability · Mathematics 2026-04-30 Yihan Zhang

We study two dual settings of information processing. Let $ \mathsf{Y} \rightarrow \mathsf{X} \rightarrow \mathsf{W} $ be a Markov chain with fixed joint probability mass function $ \mathsf{P}_{\mathsf{X}\mathsf{Y}} $ and a mutual…

Information Theory · Computer Science 2021-10-05 Michael Dikshtein , Shlomo Shamai

We prove rigorously a source coding theorem that can probably be considered folklore, a generalization to arbitrary alphabets of a problem motivated by the Information Bottleneck method. For general random variables $(Y, X)$, we show…

Information Theory · Computer Science 2018-05-02 Georg Pichler , Günther Koliander

We study discrete expressions of the form $$ T_n(g)=\sum_{i=1}^n a_i g(S_i), \qquad S_i=\sum_{j=1}^i a_j, $$ where $a_i>0$ and $\sum_{i=1}^n a_i=1$. If $g:[0,1]\to\mathbb{R}$ is a decreasing integrable function, we have $$ \sum_{i=1}^n a_i…

Classical Analysis and ODEs · Mathematics 2026-03-11 Jean-Christophe Pain

One of the main notions of information theory is the notion of mutual information in two messages (two random variables in Shannon information theory or two binary strings in algorithmic information theory). The mutual information in $x$…

Information Theory · Computer Science 2012-06-19 Ilya Razenshteyn

The role of symmetry in Boolean functions $f:\{0,1\}^n \to \{0,1\}$ has been extensively studied in complexity theory. For example, symmetric functions, that is, functions that are invariant under the action of $S_n$, is an important class…

Computational Complexity · Computer Science 2025-10-01 Sourav Chakraborty , Chandrima Kayal , Manaswi Paraashar

We study the maximal mutual information about a random variable $Y$ (representing non-private information) displayed through an additive Gaussian channel when guaranteeing that only $\epsilon$ bits of information is leaked about a random…

Information Theory · Computer Science 2016-08-16 Shahab Asoodeh , Fady Alajaji , Tamas Linder

In this paper, it is shown that the rank function of a matroid can be represented by a "mutual information function" if and only if the matroid is binary. The mutual information function considered is the one measuring the amount of…

Information Theory · Computer Science 2010-12-22 Emmanuel Abbe

Reshef et al. recently proposed a new statistical measure, the "maximal information coefficient" (MIC), for quantifying arbitrary dependencies between pairs of stochastic quantities. MIC is based on mutual information, a fundamental…

Quantitative Methods · Quantitative Biology 2015-06-12 Justin B. Kinney , Gurinder S. Atwal

Submodular functions are known to satisfy various forms of fractional subadditivity. This work investigates the conditions for equality to hold exactly or approximately in the fractional subadditivity of submodular functions. We establish…

Information Theory · Computer Science 2025-06-24 Gunank Jakhar , Gowtham R. Kurri , Suryajith Chillara , Vinod M. Prabhakaran

We study the efficiency (in terms of social welfare) of truthful and symmetric mechanisms in one-sided matching problems with {\em dichotomous preferences} and {\em normalized von Neumann-Morgenstern preferences}. We are particularly…

Computer Science and Game Theory · Computer Science 2014-09-18 Marek Adamczyk , Piotr Sankowski , Qiang Zhang

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

Given a function f: {0,1}^n \to {0,1}, the f-isomorphism testing problem requires a randomized algorithm to distinguish functions that are identical to f up to relabeling of the input variables from functions that are far from being so. An…

Data Structures and Algorithms · Computer Science 2011-12-30 Eric Blais , Amit Weinstein , Yuichi Yoshida