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Tight bounds for several symmetric divergence measures are introduced, given in terms of the total variation distance. Each of these bounds is attained by a pair of 2 or 3-element probability distributions. An application of these bounds…

Information Theory · Computer Science 2016-11-15 Igal Sason

Monotonicity with respect to all arguments is fundamental to the definition of aggregation functions. It is also a limiting property that results in many important non-monotonic averaging functions being excluded from the theoretical…

Artificial Intelligence · Computer Science 2014-08-05 Tim Wilkin , Gleb Beliakov

The Bregman divergence (Bregman distance, Bregman measure of distance) is a certain useful substitute for a distance, obtained from a well-chosen function (the "Bregman function"). Bregman functions and divergences have been extensively…

Optimization and Control · Mathematics 2019-04-10 Daniel Reem , Simeon Reich , Alvaro De Pierro

A theory of intermittency differentiation is developed for a general class of 1D Infinitely Divisible Multiplicative Chaos measures. The intermittency invariance of the underlying infinitely divisible field is established and utilized to…

Probability · Mathematics 2018-03-20 Dmitry Ostrovsky

In the paper, the author establishes inequalities, monotonicity, convexity, and unimodality for functions concerning the modified Bessel functions of the first kind and compute the completely monotonic degrees of differences between the…

Classical Analysis and ODEs · Mathematics 2014-12-02 Feng Qi

A distance mean function measures the average distance of points from the elements of a given set of points (focal set) in the space. The level sets of a distance mean function are called generalized conics. In case of infinite focal points…

Optimization and Control · Mathematics 2026-04-08 Csaba Vincze , Ábris Nagy

In this paper our aim is to prove some monotonicity and convexity results for the modified Struve function of the second kind by using its integral representation. Moreover, as consequences of these results, we present some functional…

Classical Analysis and ODEs · Mathematics 2015-01-28 Árpád Baricz , Tibor K. Pogány

In this paper we introduce a biparametric family of transformations which can be seen as an extension of the so-called up and down transformations. This new class of transformations allows to us to introduce new informational functionals,…

Information Theory · Computer Science 2025-11-05 Razvan Gabriel Iagar , David Puertas-Centeno

With any convex function F on a finite-dimensional linear space X such that F goes to infinity at infinity, we associate a Borel measure on the dual space X*. This measure is obtained by pushing forward the measure exp(-F(x))dx under the…

Functional Analysis · Mathematics 2013-04-03 Dario Cordero-Erausquin , Bo'az Klartag

This paper is devoted to the mathematical study of some divergences based on the mutual information well-suited to categorical random vectors. These divergences are generalizations of the "entropy distance" and "information distance". Their…

Statistics Theory · Mathematics 2016-08-16 Jean-François Coeurjolly , Rémy Drouilhet , Jean-François Robineau

In this paper, we introduce concepts of separable functions in balls and in the whole space, and develop a new method to investigate the qualitative properties of separable functions. We first study the axial symmetry and monotonicity of…

Analysis of PDEs · Mathematics 2018-09-18 Tao Wang , Taishan Yi

We give a systematic and thorough study of geometric notions and results connected to Minkowski's measure of symmetry and the extension of the well-known Minkowski functional to arbitrary, not necessarily symmetric convex bodies K on any…

Classical Analysis and ODEs · Mathematics 2007-05-23 Szilard Gy. Revesz

We extend the classical Lebesgue and Fubini differentiation theorems to functions of several variables, using the notions of joint derivative and joint monotonicity. Our first main result shows that for a function $f$ of bounded variation,…

Functional Analysis · Mathematics 2025-10-21 Xianrui Zhang

We study data processing inequalities that are derived from a certain class of generalized information measures, where a series of convex functions and multiplicative likelihood ratios are nested alternately. While these information…

Information Theory · Computer Science 2011-09-27 Neri Merhav

Generalization error bounds are essential to understanding machine learning algorithms. This paper presents novel expected generalization error upper bounds based on the average joint distribution between the output hypothesis and each…

Information Theory · Computer Science 2022-02-25 Gholamali Aminian , Yuheng Bu , Gregory Wornell , Miguel Rodrigues

We explore the relationship between convex and subharmonic functions on discrete sets. Our principal concern is to determine the setting in which a convex function is necessarily subharmonic. We initially consider the primary notions of…

Combinatorics · Mathematics 2014-06-25 Matthew Burke , Tony Perkins

A novel general framework for the study of $\Gamma$-convergence of functionals defined over pairs of measures and energy-measures is introduced. This theory allows us to identify the $\Gamma$-limit of these kind of functionals by knowing…

Analysis of PDEs · Mathematics 2020-04-22 Marco Caroccia , Riccardo Cristoferi

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

Divergences often play important roles for study in information science so that it is indispensable to investigate their fundamental properties. There is also a mathematical significance of such results. In this paper, we introduce some…

Statistical Mechanics · Physics 2011-10-19 S. Furuichi , F. -C. Mitroi

For continuous functions, midpoint convexity characterizes convex functions. By considering discrete versions of midpoint convexity, several types of discrete convexities of functions, including integral convexity, L$^\natural$-convexity…

Optimization and Control · Mathematics 2020-02-03 Akihisa Tamura , Kazuya Tsurumi