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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

A novel, non-trivial, probabilistic upper bound on the entropy of an unknown one-dimensional distribution, given the support of the distribution and a sample from that distribution, is presented. No knowledge beyond the support of the…

Information Theory · Computer Science 2007-07-13 Joseph DeStefano , Erik Learned-Miller

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 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

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

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

Two familiar notions of correlation are rediscovered as the extreme operating points for distributed synthesis of a discrete memoryless channel, in which a stochastic channel output is generated based on a compressed description of the…

Information Theory · Computer Science 2016-11-18 Paul Cuff

The mutual information between two jointly distributed random variables $X$ and $Y$ is a functional of the joint distribution $P_{XY},$ which is sometimes difficult to handle or estimate. A coarser description of the statistical behavior of…

Information Theory · Computer Science 2016-11-17 Yanjun Han , Or Ordentlich , Ofer Shayevitz

We derive a tight lower bound on equivocation (conditional entropy), or equivalently a tight upper bound on mutual information between a signal variable and channel outputs. The bound is in terms of the joint distribution of the signals and…

Information Theory · Computer Science 2019-01-14 Michal Hledík , Thomas R. Sokolowski , Gašper Tkačik

Two familiar notions of correlation are rediscovered as extreme operating points for simulating a discrete memoryless channel, in which a channel output is generated based only on a description of the channel input. Wyner's "common…

Information Theory · Computer Science 2008-05-02 Paul Cuff

This paper derives new bounds on the difference of the entropies of two discrete random variables in terms of the local and total variation distances between their probability mass functions. The derivation of the bounds relies on maximal…

Information Theory · Computer Science 2016-11-17 Igal Sason

We consider a setup in which Alice selects a pdf $f$ from a set of prescribed pdfs $\mathscr{P}$ and sends a prefix-free codeword $W$ to Bob in order to allow him to generate a single instance of the random variable $X\sim f$. We describe a…

Information Theory · Computer Science 2018-12-11 Cheuk Ting Li , Abbas El Gamal

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

For a closed-loop control system with a digital channel between the sensor and the controller, the notion of invariance entropy quantifies the smallest average rate of information transmission above which a given compact subset of the state…

Systems and Control · Electrical Eng. & Systems 2020-04-13 Mahendra Singh Tomar , Christoph Kawan , Pushpak Jagtap , Majid Zamani

Upper and lower bounds are obtained for the joint entropy of a collection of random variables in terms of an arbitrary collection of subset joint entropies. These inequalities generalize Shannon's chain rule for entropy as well as…

Information Theory · Computer Science 2024-05-07 Mokshay Madiman , Prasad Tetali

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

Several proofs of the monotonicity of the non-Gaussianness (divergence with respect to a Gaussian random variable with identical second order statistics) of the sum of n independent and identically distributed (i.i.d.) random variables were…

Information Theory · Computer Science 2007-07-13 Jacob Binia

This paper develops upper and lower bounds for the probability of Boolean expressions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. Our technique generalizes and extends the…

Artificial Intelligence · Computer Science 2015-03-19 Wolfgang Gatterbauer , Dan Suciu

Given a network of fixed size $n$ and an initial distribution of data, we derive sufficient connectivity conditions on a sequence of time-varying digraphs for (a) data collection and (b) data dissemination, within at most $(n-1)$…

Systems and Control · Computer Science 2016-05-03 Kevin Topley

This paper introduces the notion of exact common information, which is the minimum description length of the common randomness needed for the exact distributed generation of two correlated random variables $(X,Y)$. We introduce the quantity…

Information Theory · Computer Science 2014-02-04 Gowtham Ramani Kumar , Cheuk Ting Li , Abbas El Gamal
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