English
Related papers

Related papers: Mathematical inequalities for some divergences

200 papers

We introduce two new classes of measures of information for statistical experiments which generalise and subsume $\phi$-divergences, integral probability metrics, $\mathfrak{N}$-distances (MMD), and $(f,\Gamma)$ divergences between two or…

Machine Learning · Computer Science 2023-09-11 Robert C. Williamson , Zac Cranko

We generalize the family of $\alpha$-divergences using a pair of strictly comparable weighted means. In particular, we obtain the $1$-divergence in the limit case $\alpha\rightarrow 1$ (a generalization of the Kullback-Leibler divergence)…

Information Theory · Computer Science 2022-11-23 Frank Nielsen

We propose a new way of defining entropy of a system, which gives a general form which may be nonextensive as Tsallis entropy, but is linearly dependent on component entropies, like Renyi entropy, which is extensive. This entropy has a…

Adaptation and Self-Organizing Systems · Physics 2007-10-11 Fariel Shafee

Numerical experiments support the interesting conjecture that statistical methods be applicable not only to fully-chaotic systems, but also at the edge of chaos by using Tsallis' generalizations of the standard exponential and entropy. In…

Statistical Mechanics · Physics 2017-08-23 Marcello Lissia , Massimo Coraddu , Roberto Tonelli

This paper studies Fenchel-Young losses, a generic way to construct convex loss functions from a regularization function. We analyze their properties in depth, showing that they unify many well-known loss functions and allow to create…

Machine Learning · Statistics 2019-02-25 Mathieu Blondel , André F. T. Martins , Vlad Niculae

In this paper we shall consider one parametric generalization of some non-symmetric divergence measures. The \textit{non-symmetric divergence measures} are such as: Kullback-Leibler \textit{relative information}, $\chi…

Statistics Theory · Mathematics 2007-06-13 Pranesh Kumar , Inder Jeet Taneja

It is shown that the distribution derived from the principle of maximum Tsallis entropy is a superposable Levy-type distribution. Concomitantly, the leading order correction to the limit distribution is also deduced. This demonstration…

Statistical Mechanics · Physics 2007-05-23 Sumiyoshi Abe , A. K. Rajagopal

We have calculated the Tsallis entropy and Fisher information matrix (entropy) of spatially-correlated nonextensive systems, by using an analytic non-Gaussian distribution obtained by the maximum entropy method. Effects of the correlated…

Statistical Mechanics · Physics 2009-11-13 Hideo Hasegawa

The minimum rate needed to accurately approximate a product distribution based on an unnormalized informational divergence is shown to be a mutual information. This result subsumes results of Wyner on common information and Han-Verd\'{u} on…

Information Theory · Computer Science 2013-05-14 Jie Hou , Gerhard Kramer

The purpose of this note is to argue that degree of nonextensivity as given by Tsallis distribution obtained from maximum entropy principle has a different origin than nonextensivity inferred from pseudo-additive property of Tsallis…

Statistical Mechanics · Physics 2007-05-23 Ramandeep S. Johal

Probability distributions defined on the half space are known to be quite different from those in the full space. Here, a nonextensive entropic treatment is presented for the half space in an analytic and self-consistent way. In this…

Statistical Mechanics · Physics 2007-05-23 A. K. Rajagopal , Sumiyoshi Abe

We study the geometry of probability distributions with respect to a generalized family of Csisz\'ar $f$-divergences. A member of this family is the relative $\alpha$-entropy which is also a R\'enyi analog of relative entropy in information…

Information Theory · Computer Science 2020-05-26 M. Ashok Kumar , Kumar Vijay Mishra

The Tsallis entropy and Fisher information entropy (matrix) are very important quantities expressing information measures in nonextensive systems. Stationary and dynamical properties of the information entropies have been investigated in…

Statistical Mechanics · Physics 2009-11-13 Hideo Hasegawa

Entropy is useful in statistical problems as a measure of irreversibility, randomness, mixing, dispersion, and number of microstates. However, there remains ambiguity over the precise mathematical formulation of entropy, generalized beyond…

Statistical Mechanics · Physics 2023-08-21 Vladimir Zhdankin

We discuss some inequalities for N nonnegative numbers. We use these inequalities to obtain known inequalities for probability distributions and new entropic and information inequalities for quantum tomograms of qudit states. The…

Quantum Physics · Physics 2013-07-04 Margarita A. Man'ko , Vladimir I. Man'ko

Our aim is to provide a short and self contained synthesis which generalise and unify various related and unrelated works involving what we call Phi-Sobolev functional inequalities. Such inequalities related to Phi-entropies can be seen in…

Probability · Mathematics 2021-11-30 Djalil Chafai

In this paper we have shall generalize Shearer's entropy inequality and its recent extensions by Madiman and Tetali, and shall apply projection inequalities to deduce extensions of some of the inequalities concerning sums of sets of…

Combinatorics · Mathematics 2017-01-10 Paul Balister , Béla Bollobás

We propose a one-parameter family \ $\mathbb{R}_q$ \ of deformations of the reals, which is motivated by the generalized additivity of the Tsallis entropy. We introduce a generalized multiplication which is distributive with respect to the…

Mathematical Physics · Physics 2015-05-27 Nikos Kalogeropoulos

We introduce a new transformation called \emph{relative differential-escort}, which extends the usual differential-escort transformation by relating the change of variable to a reference probability density. As an application of it, we…

Mathematical Physics · Physics 2025-07-24 Razvan Gabriel Iagar , David Puertas-Centeno , Elio V. Toranzo

New upper bounds on the relative entropy are derived as a function of the total variation distance. One bound refines an inequality by Verd\'{u} for general probability measures. A second bound improves the tightness of an inequality by…

Information Theory · Computer Science 2015-04-14 Igal Sason
‹ Prev 1 8 9 10 Next ›