English
Related papers

Related papers: A Variational Formula for Infinity-R\'{e}nyi Diver…

200 papers

Information theoretic leakage metrics quantify the amount of information about a private random variable $X$ that is leaked through a correlated revealed variable $Y$. They can be used to evaluate the privacy of a system in which an…

Information Theory · Computer Science 2025-05-15 Sophie Taylor , Praneeth Kumar Vippathalla , Justin P. Coon

Universal hash functions map the output of a source to random strings over a finite alphabet, aiming to approximate the uniform distribution on the set of strings. A classic result on these functions, called the Leftover Hash Lemma, gives…

Information Theory · Computer Science 2026-01-05 Madhura Pathegama , Alexander Barg

Differential privacy is a notion of privacy that has become very popular in the database community. Roughly, the idea is that a randomized query mechanism provides sufficient privacy protection if the ratio between the probabilities that…

Cryptography and Security · Computer Science 2014-06-18 Mário S. Alvim , Miguel E. Andrés , Konstantinos Chatzikokolakis , Pierpaolo Degano , Catuscia Palamidessi

The aim of this work is to provide bounds connecting two probability measures of the same event using R\'enyi $\alpha$-Divergences and Sibson's $\alpha$-Mutual Information, a generalization of respectively the Kullback-Leibler Divergence…

Information Theory · Computer Science 2020-01-20 Amedeo Roberto Esposito , Michael Gastpar , Ibrahim Issa

This paper investigates the so-called leakage effect of trading strategies generated functionally from rank-dependent portfolio generating functions. This effect measures the loss in wealth of trading strategies due to renewing the…

Portfolio Management · Quantitative Finance 2019-12-10 Kangjianan Xie

Opacity is a general language-theoretic framework in which several security properties of a system can be expressed. Its parameters are a predicate, given as a subset of runs of the system, and an observation function, from the set of runs…

Cryptography and Security · Computer Science 2019-02-20 B. Bérard , J. Mullins , M. Sassolas

We extend the duality between exponential integrals and relative entropy to a variational formula for exponential integrals involving the Renyi divergence. This formula characterizes the dependence of risk-sensitive functionals and related…

Probability · Mathematics 2013-10-25 Rami Atar , Kamaljit Chowdhary , Paul Dupuis

We consider the maximum entropy problems associated with R\'enyi $Q$-entropy, subject to two kinds of constraints on expected values. The constraints considered are a constraint on the standard expectation, and a constraint on the…

Information Theory · Computer Science 2008-12-18 Jean-François Bercher

We provide the sandwiched R\'enyi divergence of order $\alpha\in(\frac{1}{2},1)$, as well as its induced quantum information quantities, with an operational interpretation in the characterization of the exact strong converse exponents of…

Quantum Physics · Physics 2024-05-29 Ke Li , Yongsheng Yao

Recently, varextropy has been introduced as a new dispersion index and a measure of information. In this article, we derive the generating function of extropy and present its infinite series representation. Furthermore, we propose new…

Statistics Theory · Mathematics 2025-12-12 Faranak Goodarzi , Somayeh Ghafouri

Maximal leakage quantifies the leakage of information from data $X \in \mathcal{X}$ due to an observation $Y$. While fundamental properties of maximal leakage, such as data processing, sub-additivity, and its connection to mutual…

Information Theory · Computer Science 2025-12-24 Anuran Makur , Japneet Singh

We propose an extension of the classical R\'enyi divergences to quantum states through an optimization over probability distributions induced by restricted sets of measurements. In particular, we define the notion of locally-measured…

Quantum Physics · Physics 2025-10-10 Tobias Rippchen , Sreejith Sreekumar , Mario Berta

We investigate the problem of guessing a discrete random variable $Y$ under a privacy constraint dictated by another correlated discrete random variable $X$, where both guessing efficiency and privacy are assessed in terms of the…

Information Theory · Computer Science 2017-04-13 Shahab Asoodeh , Mario Diaz , Fady Alajaji , Tamás Linder

We address the problem of uncertainty quantification and propose measures of total, aleatoric, and epistemic uncertainty based on a known decomposition of (strictly) proper scoring rules, a specific type of loss function, into a divergence…

Machine Learning · Computer Science 2025-05-29 Paul Hofman , Yusuf Sale , Eyke Hüllermeier

This paper provides tight bounds on the R\'enyi entropy of a function of a discrete random variable with a finite number of possible values, where the considered function is not one-to-one. To that end, a tight lower bound on the R\'enyi…

Information Theory · Computer Science 2018-12-11 Igal Sason

This paper introduces the variational R\'enyi bound (VR) that extends traditional variational inference to R\'enyi's alpha-divergences. This new family of variational methods unifies a number of existing approaches, and enables a smooth…

Machine Learning · Statistics 2016-10-31 Yingzhen Li , Richard E. Turner

We introduce a privacy measure called statistic maximal leakage that quantifies how much a privacy mechanism leaks about a specific secret, relative to the adversary's prior information about that secret. Statistic maximal leakage is an…

Information Theory · Computer Science 2024-11-28 Shuaiqi Wang , Zinan Lin , Giulia Fanti

We define a new divergence of von Neumann algebras using a variational expression that is similar in nature to Kosaki's formula for the relative entropy. Our divergence satisfies the usual desirable properties, upper bounds the sandwiched…

Quantum Physics · Physics 2021-11-17 Stefan Hollands

We study the problem of data disclosure with privacy guarantees, wherein the utility of the disclosed data is ensured via a \emph{hard distortion} constraint. Unlike average distortion, hard distortion provides a deterministic guarantee of…

Information Theory · Computer Science 2018-06-04 Jiachun Liao , Oliver Kosut , Lalitha Sankar , Flavio P. Calmon

For a random variable we can define a variational relationship with practical physical meaning as dI=dbar(x)-bar(dx), where I is called as uncertainty measurement. With the help of a generalized definition of expectation,…

Statistical Mechanics · Physics 2008-10-27 Congjie Ou , Aziz El Kaabouchi , Alain Le Mehaute , Qiuping A. Wang , Jincan Chen