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The two most prevalent notions of common information (CI) are due to Wyner and Gacs-Korner and both the notions can be stated as two different characteristic points in the lossless Gray-Wyner region. Although the information theoretic…

Information Theory · Computer Science 2014-04-01 Kumar Viswanatha , Emrah Akyol , Kenneth Rose

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

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

Measuring the relationship between any pair of variables is a rich and active area of research that is central to scientific practice. In contrast, characterizing the common information among any group of variables is typically a…

Machine Learning · Statistics 2017-06-20 Greg Ver Steeg , Shuyang Gao , Kyle Reing , Aram Galstyan

In literature, different common informations were defined by G\'acs and K\"orner, by Wyner, and by Kumar, Li, and Gamal, respectively. In this paper, we define two generalized versions of common informations, named approximate and exact…

Information Theory · Computer Science 2017-07-26 Lei Yu , Houqiang Li , Chang Wen Chen

This paper generalizes Wyner's definition of common information of a pair of random variables to that of $N$ random variables. We prove coding theorems that show the same operational meanings for the common information of two random…

Information Theory · Computer Science 2010-10-19 Wei Liu , Ge Xu , Biao Chen

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

We explore the duality between the simulation and extraction of secret correlations in light of a similar well-known operational duality between the two notions of common information due to Wyner, and G\'acs and K\"orner. For the inverse…

Information Theory · Computer Science 2015-06-02 Pradeep Kr. Banerjee

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 propose a notion of common information that allows one to quantify and separate the information that is shared between two random variables from the information that is unique to each. Our notion of common information is defined by an…

Machine Learning · Computer Science 2023-11-07 Michael Kleinman , Alessandro Achille , Stefano Soatto , Jonathan Kao

In this paper we generalize the notion of common information of two dependent variables introduced by G\'acs & K\"orner. They defined common information as the largest entropy rate of a common random variable two parties observing one of…

Information Theory · Computer Science 2016-11-17 Vinod M. Prabhakaran , Manoj M. Prabhakaran

Secure multi-party computation is a central problem in modern cryptography. An important sub-class of this are problems of the following form: Alice and Bob desire to produce sample(s) of a pair of jointly distributed random variables. Each…

Information Theory · Computer Science 2010-02-10 Vinod Prabhakaran , Manoj Prabhakaran

The information that two random variables $Y$, $Z$ contain about a third random variable $X$ can have aspects of shared information (contained in both $Y$ and $Z$), of complementary information (only available from $(Y,Z)$ together) and of…

Information Theory · Computer Science 2015-03-05 Johannes Rauh , Nils Bertschinger , Eckehard Olbrich , Jürgen Jost

We take a closer look at the structure of bivariate dependency induced by a pair of predictor random variables $(X_1, X_2)$ trying to synergistically, redundantly or uniquely encode a target random variable $Y$. We evaluate a recently…

Information Theory · Computer Science 2015-03-03 Pradeep Kr. Banerjee

A new bimodal generative model is proposed for generating conditional and joint samples, accompanied with a training method with learning a succinct bottleneck representation. The proposed model, dubbed as the variational Wyner model, is…

Machine Learning · Computer Science 2022-07-29 J. Jon Ryu , Yoojin Choi , Young-Han Kim , Mostafa El-Khamy , Jungwon Lee

The exact common information between a set of random variables $X_1,...,X_n$ is defined as the minimum entropy of a shared random variable that allows for the exact distributive simulation of $X_1,...,X_n$. It has been established that, in…

Information Theory · Computer Science 2024-07-09 Osama Hanna , Xinlin Li , Suhas Diggavi , Christina Fragouli

We study secure source-coding with causal disclosure, under the Gaussian distribution. The optimality of Gaussian auxiliary random variables is shown in various scenarios. We explicitly characterize the tradeoff between the rates of…

Information Theory · Computer Science 2015-06-16 Sanket Satpathy , Paul Cuff

Consider a multi-source network coding problem with correlated sources. While the fundamental limits are known, achieving them, in general, involves a computational burden due to the complex decoding process. Efficient solutions, on the…

Information Theory · Computer Science 2016-01-27 Salman Salamatian , Asaf Cohen , Muriel Médard

Many computer vision tasks share substantial overlapping information, yet conventional codecs tend to ignore this, leading to redundant and inefficient representations. The Gray-Wyner network, a classical concept from information theory,…

Machine Learning · Computer Science 2026-05-11 Anderson de Andrade , Alon Harell , Ivan V. Bajić

We introduce the coordination principle, which states that perfect coordination, in the form of agreement on a uniformly random output, among N parties is possible only if they share a common cause. This principle is purely causal and can…

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