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Related papers: Concavity of entropy under thinning

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We study the convexity of the entropy functional along particular interpolating curves defined on the space of finitely supported probability measures on a graph.

Probability · Mathematics 2014-06-20 Erwan Hillion

In this paper, I expand Shannon's definition of entropy into a new form of entropy that allows integration of information from different random events. Shannon's notion of entropy is a special case of my more general definition of entropy.…

Machine Learning · Computer Science 2008-11-04 Stefan Jaeger

In this simple article, with possible applications in theoretical and applied physics, we suggest an original way to derive the expression of Shannon's entropy from a purely variational approach,using constraints. Based on the work of Edwin…

Statistical Mechanics · Physics 2021-07-13 Thomas Cailleteau

The entropy region is constructed from vectors of random variables by collecting Shannon entropies of all subvectors. Its shape is studied here by means of polymatroidal constructions, notably by convolution. The closure of the region is…

Information Theory · Computer Science 2013-10-23 František Matúš , Lászlo Csirmaz

Maximum likelihood estimation of a log-concave probability density is formulated as a convex optimization problem and shown to have an equivalent dual formulation as a constrained maximum Shannon entropy problem. Closely related maximum…

Methodology · Statistics 2010-11-16 Roger Koenker , Ivan Mizera

We use complex contour integral techniques to study the entropy H and subentropy Q as functions of the elementary symmetric polynomials, revealing a series of striking properties. In particular for these variables, derivatives of -Q are…

Quantum Physics · Physics 2013-10-25 Richard Jozsa , Graeme Mitchison

An "entropy increasing to the maximum" result analogous to the entropic central limit theorem (Barron 1986; Artstein et al. 2004) is obtained in the discrete setting. This involves the thinning operation and a Poisson limit. Monotonic…

Information Theory · Computer Science 2009-11-18 Yaming Yu

Many partially-successful attempts have been made to find the most natural discrete-variable version of Shannon's entropy power inequality (EPI). We develop an axiomatic framework from which we deduce the natural form of a discrete-variable…

Information Theory · Computer Science 2016-11-17 Saikat Guha , Jeffrey H. Shapiro , Raul Garcia-Patron Sanchez

When two independent analog signals, X and Y are added together giving Z=X+Y, the entropy of Z, H(Z), is not a simple function of the entropies H(X) and H(Y), but rather depends on the details of X and Y's distributions. Nevertheless, the…

Quantum Physics · Physics 2014-02-21 Robert Koenig , Graeme Smith

The entropy power inequality, which plays a fundamental role in information theory and probability, may be seen as an analogue of the Brunn-Minkowski inequality. Motivated by this connection to Convex Geometry, we survey various recent…

Information Theory · Computer Science 2020-02-07 Mokshay Madiman , James Melbourne , Peng Xu

We show that classical chaining bounds on the suprema of random processes in terms of entropy numbers can be systematically improved when the underlying set is convex: the entropy numbers need not be computed for the entire set, but only…

Probability · Mathematics 2023-09-18 Ramon van Handel

We present a unifying approach to the study of entropies in Mathematics, such as measure entropy, topological entropy, algebraic entropy, set-theoretic entropy. We take into account discrete dynamical systems, that is, pairs $(X,T)$, where…

Dynamical Systems · Mathematics 2019-08-30 Dikran Dikranjan , Anna Giordano Bruno

We study the class of self-similar probability density functions with finite mean and variance which maximize R\'{e}nyi's entropy. The investigation is restricted in the Schwartz space $S(\mathbb{R}^d)$ and in the space of…

Mathematical Physics · Physics 2015-10-28 Agapitos N. Hatzinikitas

We introduce hardness in relative entropy, a new notion of hardness for search problems which on the one hand is satisfied by all one-way functions and on the other hand implies both next-block pseudoentropy and inaccessible entropy, two…

Cryptography and Security · Computer Science 2024-11-15 Rohit Agrawal , Yi-Hsiu Chen , Thibaut Horel , Salil Vadhan

We give a transport proof of a discrete version of the displacement convexity of entropy on integers (Z), and get, as a consequence, two discrete forms of the Pr{\'e}kopa-Leindler Inequality : the Four Functions Theorem of Ahlswede and…

Probability · Mathematics 2019-05-13 Nathael Gozlan , Cyril Roberto , Paul-Marie Samson , Prasad Tetali

The entanglement entropy of a subsystem of a quantum system is expressed, in the replica approach, through analytic continuation with respect to n of the trace of the n-th power of the reduced density matrix. This trace can be thought of as…

High Energy Physics - Theory · Physics 2008-12-18 Michele Caraglio , Ferdinando Gliozzi

The joint convexity of the map $(X,A) \mapsto X^* A^{-1} X$, an integral representation of operator convex functions, and an observation of Ando are used to obtain a simple proof of both the joint convexity of relative entropy and a trace…

Quantum Physics · Physics 2022-09-07 Mary Beth Ruskai

Entropy functionals (i.e. convex integral functionals) and extensions of these functionals are minimized on convex sets. This paper is aimed at reducing as much as possible the assumptions on the constraint set. Dual equalities and…

Optimization and Control · Mathematics 2015-05-13 Christian Léonard

The entropy per coordinate in a log-concave random vector of any dimension with given density at the mode is shown to have a range of just 1. Uniform distributions on convex bodies are at the lower end of this range, the distribution with…

Information Theory · Computer Science 2024-05-07 Sergey Bobkov , Mokshay Madiman

Convergence properties of Shannon Entropy are studied. In the differential setting, it is shown that weak convergence of probability measures, or convergence in distribution, is not enough for convergence of the associated differential…

Information Theory · Computer Science 2016-11-18 Francisco J. Piera , Patricio Parada