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Comparative convexity is a generalization of convexity relying on abstract notions of means. We define the Jensen divergence and the Jensen diversity from the viewpoint of comparative convexity, and show how to obtain the generalized…

Information Theory · Computer Science 2017-05-05 Frank Nielsen , Richard Nock

We give the Choi-Davis-Jensen type inequality without using convexity. Applying our main results, we also give new inequalities improving previous known results. In particular, we show some inequalities for relative operator entropies and…

Functional Analysis · Mathematics 2018-01-31 Jadranka Mićić , Hamid Reza Moradi , Shigeru Furuichi

Since its original formulation, Jensen's inequality has played a fundamental role across mathematics, statistics, and machine learning, with its probabilistic version highlighting the nonnegativity of the so-called Jensen's gap, i.e., the…

Machine Learning · Computer Science 2025-11-11 Marcin Mazur , Tadeusz Dziarmaga , Piotr Kościelniak , Łukasz Struski

Feature selection is a key step when dealing with high dimensional data. In particular, these techniques simplify the process of knowledge discovery from the data by selecting the most relevant features out of the noisy, redundant and…

Machine Learning · Computer Science 2024-02-09 Alaiz-Rodriguez , R. , Parnell , A. C

The goal of this note is to show that some convolution type inequalities from Harmonic Analysis and Information Theory, such as Young's convolution inequality (with sharp constant), Nelson's hypercontractivity of the Hermite semi-group or…

Functional Analysis · Mathematics 2009-07-17 Dario Cordero-Erausquin , Michel Ledoux

There are three classical divergence measures exist in the literature on information theory and statistics. These are namely, Jeffryes-Kullback-Leiber J-divergence. Sibson-Burbea-Rao Jensen-Shannon divegernce and Taneja arithemtic-geometric…

Information Theory · Computer Science 2011-09-27 Inder Jeet Taneja

In transfer learning, training and testing data sets are drawn from different data distributions. The transfer generalization gap is the difference between the population loss on the target data distribution and the training loss. The…

Machine Learning · Computer Science 2021-01-26 Sharu Theresa Jose , Osvaldo Simeone

In this paper, using some aspects of convex functions, we refine discrete Jensen's inequality via weight functions. Then, using these results, we give some applications in different abstract spaces and obtain some new interesting…

Numerical Analysis · Mathematics 2007-05-23 Jamal Rooin

The concept of Jeans gravitational instability is rediscussed in the framework of nonextensive statistics and its associated kinetic theory. A simple analytical formula generalizing the Jeans criterion is derived by assuming that the…

Astrophysics · Physics 2009-11-07 J. A. S. Lima , R. Silva , J. Santos

This paper proposes a new sharpened version of the Jensen's inequality. The proposed new bound is simple and insightful, is broadly applicable by imposing minimum assumptions, and provides fairly accurate result in spite of its simple form.…

Statistics Theory · Mathematics 2017-10-26 J. G. Liao , Arthur Berg

The Jensen's inequality plays a crucial role in the analysis of time-delay and sampled-data systems. Its conservatism is studied through the use of the Gr\"{u}ss Inequality. It has been reported in the literature that fragmentation (or…

Systems and Control · Computer Science 2012-04-06 Corentin Briat

We introduce a refinement to the convex split lemma by replacing the max mutual information with the collision mutual information, transforming the inequality into an equality. This refinement yields tighter achievability bounds for quantum…

Quantum Physics · Physics 2025-02-18 Gilad Gour

Most quantum divergences derive their structure from classical f-divergences or Renyi-type constructions, a dependence that obscures several quantum geometric effects. We introduce a quantum relative-alpha-entropy that extends Umegaki's…

Quantum Physics · Physics 2026-04-09 Sayantan Roy , Atin Gayen , Aditi Kar Gangopadhyay , Sugata Gangopadhyay

Some new inequalities of Karamata type are established with a convex function in this paper. The methods of our proof allow us to obtain an extended version of the reverse of Jensen inequality given by Pe{\v} cari\'c and Mi\'ci\'c. Applying…

Mathematical Physics · Physics 2019-05-24 Shigeru Furuichi , Hamid Reza Moradi , Akram Zardadi

We examine the problem of controlling divergences for latent space regularisation in variational autoencoders. Specifically, when aiming to reconstruct example $x\in\mathbb{R}^{m}$ via latent space $z\in\mathbb{R}^{n}$ ($n\leq m$), while…

Machine Learning · Computer Science 2021-01-05 Jacob Deasy , Nikola Simidjievski , Pietro Liò

We show that an information-theoretic property of Shannon's entropy power, known as concavity of entropy power, can be fruitfully employed to prove inequalities in sharp form. In particular, the concavity of entropy power implies the…

Information Theory · Computer Science 2012-07-13 Giuseppe Toscani

In this paper the Jessen's type inequality for normalized positive $C_0$-semigroups is obtained. An adjoint of Jessen's type inequality has also been derived for the corresponding adjoint-semigroup, which does not give the analogous results…

Functional Analysis · Mathematics 2015-04-08 Gul I hina Aslam , Matloob Anwar

Whereas Shannon entropy is related to the growth rate of multinomial coefficients, we show that the quadratic entropy (Tsallis 2-entropy) is connected to their $q$-deformation; when $q$ is a prime power, these $q$-multinomial coefficients…

Mathematical Physics · Physics 2020-03-27 Juan Pablo Vigneaux

This article proposes a new two-parameter generalized entropy, which can be reduced to the Tsallis and the Shannon entropy for specific values of its parameters. We develop a number of information-theoretic properties of this generalized…

Mathematical Physics · Physics 2024-05-02 Supriyo Dutta , Shigeru Furuichi , Partha Guha

We give a truly elementary proof of the convexity of metric adjusted skew information following an idea of Effros. We extend earlier results of weak forms of superadditivity to general metric adjusted skew informations. Recently, Luo and…

Mathematical Physics · Physics 2012-10-02 Liang Cai , Frank Hansen