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The matrix-based R\'enyi's entropy allows us to directly quantify information measures from given data, without explicit estimation of the underlying probability distribution. This intriguing property makes it widely applied in statistical…

Machine Learning · Computer Science 2022-12-01 Yuxin Dong , Tieliang Gong , Shujian Yu , Hong Chen , Chen Li

Shannon entropy and Fisher information functionals are known to quantify certain information-theoretic properties of continuous probability distributions of various origins. We carry out a systematic study of these functionals, while…

Quantum Physics · Physics 2007-05-23 Piotr Garbaczewski

We show that the new quantum extension of Renyi's \alpha-relative entropies, introduced recently by Muller-Lennert, Dupuis, Szehr, Fehr and Tomamichel, J. Math. Phys. 54, 122203, (2013), and Wilde, Winter, Yang, Commun. Math. Phys. 331,…

Quantum Physics · Physics 2015-02-17 Milan Mosonyi , Tomohiro Ogawa

Entropies are fundamental measures of uncertainty with central importance in information theory and statistics and applications across all the quantitative sciences. Under a natural set of operational axioms, the most general form of…

Information Theory · Computer Science 2026-02-02 Roberto Rubboli , Erkka Haapasalo , Marco Tomamichel

We show that a meaningful statistical description is possible in conservative and mixing systems with zero Lyapunov exponent in which the dynamical instability is only linear in time. More specifically, (i) the sensitivity to initial…

Statistical Mechanics · Physics 2009-11-11 Giulio Casati , Constantino Tsallis , Fulvio Baldovin

This paper deals with the Fisher-consistency, weak continuity and differentiability of estimating functionals corresponding to a class of both linear and nonlinear regression high breakdown M estimates, which includes S and MM estimates. A…

Statistics Theory · Mathematics 2012-11-26 María V. Fasano , Ricardo A. Maronna , Mariela Sued , Víctor J. Yohai

The huge amount of available data nowadays is a challenge for kernel-based machine learning algorithms like SVMs with respect to runtime and storage capacities. Local approaches might help to relieve these issues and to improve statistical…

Machine Learning · Statistics 2019-03-05 Florian Dumpert

Isotropic $\alpha$-stable distributions are central in the theory of heavy-tailed distributions and play a role similar to that of the Gaussian density among finite second-moment laws. Given a sequence of $n$ observations, we are interested…

Information Theory · Computer Science 2024-12-20 Jihad Fahs , Ibrahim Abou-Faycal , Ibrahim Issa

Two-sided bounds are explored for concentration functions and R\'enyi entropies in the class of discrete log-concave probability distributions. They are used to derive certain variants of the entropy power inequalities.

Probability · Mathematics 2021-04-27 Sergey G. Bobkov , Arnaud Marsiglietti , James Melbourne

Quantum conditional entropies play a fundamental role in quantum information theory. In quantum key distribution, they are exploited to obtain reliable lower bounds on the secret-key rates in the finite-size regime, against collective…

Quantum Physics · Physics 2026-03-05 Gabriele Staffieri , Giovanni Scala , Cosmo Lupo

Husimi function (Q-function) of a quantum state is the distribution function of the density operator in the coherent state representation. It is widely used in theoretical research, such as in quantum optics. The Wehrl entropy is the…

Quantum Physics · Physics 2025-07-14 Chen Xu , Yiqi Yu , Peng Zhang

A random vector ${\bf X}$ is weakly stable iff for all $a,b \in \mathbb{R}$ there exists a random variable $\Theta$ such that $a{\bf X} + b {\bf X}' \stackrel{d}{=} {\bf X} \Theta$, where $X'$ is an independent copy of $X$ and $\Theta$ is…

Probability · Mathematics 2014-07-16 B. H. Jasiulis-Gołdyn , J. K. Misiewicz

We consider distributions of ordered random vectors with given one-dimensional marginal distributions. We give an elementary necessary and sufficient condition for the existence of such a distribution with finite entropy. In this case, we…

Statistics Theory · Mathematics 2015-09-08 Cristina Butucea , Jean-François Delmas , Anne Dutfoy , Richard Fischer

The Tukey-$\lambda$ distribution has interesting properties including (i) for some parameters values it has finite support, and for others infinite support, and (ii) it can mimic several other distributions such that parameter estimation…

Statistics Theory · Mathematics 2020-12-14 Matthew Roughan

Consider a measure-preserving transition kernel $T$ on an arbitrary probability space $(\mathbb X,\mathcal cA,\pi)$. In this level of generality, we prove that a one-step hyper-contractivity estimate of the form $\|T\|_{p\to q}\le 1$ with…

Probability · Mathematics 2026-02-20 Justin Salez

We address the construction of stable random matrix ensembles as the generalization of the stable random variables (Levy distributions). With a simple method we derive the Cauchy case, which is known to have remarkable properties. These…

Statistical Mechanics · Physics 2007-05-23 M. Tierz

Escort distributions have been shown to be very useful in a great variety of fields ranging from information theory, nonextensive statistical mechanics till coding theory, chaos and multifractals. In this work we give the notion and the…

Mathematical Physics · Physics 2018-12-26 D. Puertas-Centeno

We study the distribution of sequences of the form $(q_ny)_{n=1}^\infty$, where $(q_n)_{n=1}^\infty$ is some increasing sequence of integers. In particular, we study the Lebesgue measure and find bounds on the Hausdorff dimension of the set…

Number Theory · Mathematics 2024-11-20 S. Kristensen , T. Persson

The diverse range of resources which underlie the utility of quantum states in practical tasks motivates the development of universally applicable methods to measure and compare resources of different types. However, many of such approaches…

Quantum Physics · Physics 2021-03-19 Bartosz Regula , Ludovico Lami , Giovanni Ferrari , Ryuji Takagi

Distributional assumptions have been shown to be necessary for the robust learnability of concept classes when considering the exact-in-the-ball robust risk and access to random examples by Gourdeau et al. (2019). In this paper, we study…

Machine Learning · Computer Science 2023-07-21 Pascale Gourdeau , Varun Kanade , Marta Kwiatkowska , James Worrell