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Recently, two extensions of Wyner's common information\textemdash exact and R\'enyi common informations\textemdash were introduced respectively by Kumar, Li, and El Gamal (KLE), and the present authors. The class of common information…

Information Theory · Computer Science 2020-02-18 Lei Yu , Vincent Y. F. Tan

In this note, we provide analytic expressions for the R\'enyi common information of orders in $(1,\infty)$ for the doubly symmetric binary source (DSBS). Until now, analytic expressions for the R\'enyi common information of all orders in…

Information Theory · Computer Science 2024-07-09 Lei Yu

We study a generalized version of Wyner's common information problem (also coined the distributed source simulation problem). The original common information problem consists in understanding the minimum rate of the common input to…

Information Theory · Computer Science 2019-12-04 Lei Yu , Vincent Y. F. Tan

An important notion of common information between two random variables is due to Wyner. In this paper, we derive a lower bound on Wyner's common information for continuous random variables. The new bound improves on the only other general…

Information Theory · Computer Science 2021-02-17 Erixhen Sula , Michael Gastpar

We study communication systems over band-limited Additive White Gaussian Noise (AWGN) channels in which the transmitter output is constrained to be symmetric binary (bi-polar). In this work we improve the original Ozarov-Wyner-Ziv (OWZ)…

Information Theory · Computer Science 2021-10-07 Michael Peleg , Tomer Michaeli , Shlomo Shamai

A family of skew information quantities is obtained, in which the well-known Wigner-Yanase skew information and quantum Fisher information stand as special cases. A transparent proof of convexity of the generalized skew information is…

Quantum Physics · Physics 2023-06-14 Ma-Cheng Yang , Cong-Feng Qiao

Wyner's common information was originally defined for a pair of dependent discrete random variables. Its significance is largely reflected in, hence also confined to, several existing interpretations in various source coding problems. This…

Information Theory · Computer Science 2013-01-11 Ge Xu , Wei Liu , Biao Chen

Common information (CI) is ubiquitous in information theory and related areas such as theoretical computer science and discrete probability. However, because there are multiple notions of CI, a unified understanding of the deep…

Information Theory · Computer Science 2022-11-04 Lei Yu , Vincent Y. F. Tan

We propose a framework for second-order achievability, called type deviation convergence, that is generally applicable to settings in network information theory, and is especially suitable for lossy source coding and channel coding with…

Information Theory · Computer Science 2025-10-24 Xiang Li , Cheuk Ting Li

This paper introduces "swiveled Renyi entropies" as an alternative to the Renyi entropic quantities put forward in [Berta et al., Phys. Rev. A 91, 022333 (2015)]. What distinguishes the swiveled Renyi entropies from the prior proposal of…

Quantum Physics · Physics 2016-03-22 Frédéric Dupuis , Mark M. Wilde

This paper presents a novel theoretical study of the general problem of multiple source adaptation using the notion of Renyi divergence. Our results build on our previous work [12], but significantly broaden the scope of that work in…

Machine Learning · Computer Science 2012-05-14 Yishay Mansour , Mehryar Mohri , Afshin Rostamizadeh

We evaluate the asymptotics of equivocations, their exponents as well as their second-order coding rates under various R\'{e}nyi information measures. Specifically, we consider the effect of applying a hash function on a source and we…

Information Theory · Computer Science 2016-07-06 Masahito Hayashi , Vincent Y. F. Tan

An uncertainty relation for the R\'enyi entropies of conjugate quantum observables is used to obtain a strong Heisenberg limit of the form ${\rm RMSE} \geq f(\alpha)/(\langle N\rangle+\frac12)$, bounding the root mean square error of any…

Quantum Physics · Physics 2022-11-21 Michael J. W. Hall

R\'enyi divergence is related to R\'enyi entropy much like information divergence (also called Kullback-Leibler divergence or relative entropy) is related to Shannon's entropy, and comes up in many settings. It was introduced by R\'enyi as…

Information Theory · Computer Science 2010-05-28 Tim van Erven , Peter Harremoës

We present a new notion $R_\ell$ of higher-order common information, which quantifies the information that $\ell\geq 2$ arbitrarily distributed random variables have in common. We provide analytical lower bounds on $R_3$ and $R_4$ for…

Information Theory · Computer Science 2024-06-05 Jan Østergaard

Bounds on information combining are entropic inequalities that determine how the information, or entropy, of a set of random variables can change when they are combined in certain prescribed ways. Such bounds play an important role in…

Information Theory · Computer Science 2020-11-10 Christoph Hirche

Bounds on information combining are a fundamental tool in coding theory, in particular when analyzing polar codes and belief propagation. They usually bound the evolution of random variables with respect to their Shannon entropy. In recent…

Information Theory · Computer Science 2023-05-05 Christoph Hirche , Xinyue Guan , Marco Tomamichel

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

We investigate quantum R\'enyi entropic quantities, specifically those derived from 'sandwiched' divergence. This divergence is one of several proposed R\'enyi generalisations of the quantum relative entropy. We may define R\'enyi…

Quantum Physics · Physics 2021-10-04 Alexander McKinlay

The R\'enyi information measures are characterized in terms of their Shannon counterparts, and properties of the former are recovered from first principle via the associated properties of the latter. Motivated by this characterization, a…

Information Theory · Computer Science 2016-03-14 Ofer Shayevitz
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