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We consider the problem of source coding with receiver side information for the simple network proposed by R. Gray and A. Wyner in 1974. In this network, a transmitter must reliably transport the output of two correlated information sources…

Information Theory · Computer Science 2008-05-28 R. Timo , A. Grant , T. Chan , G. Kramer

Information decompositions quantify how the Shannon information about a given random variable is distributed among several other random variables. Various requirements have been proposed that such a decomposition should satisfy, leading to…

Information Theory · Computer Science 2023-07-11 Johannes Rauh , Pradeep Kr. Banerjee , Eckehard Olbrich , Guido Montúfar , Jürgen Jost

We give an information-theoretic interpretation of Canonical Correlation Analysis (CCA) via (relaxed) Wyner's common information. CCA permits to extract from two high-dimensional data sets low-dimensional descriptions (features) that…

Information Theory · Computer Science 2020-03-02 Michael Gastpar , Erixhen Sula

In physics we often use very simple models to describe systems with many degrees of freedom, but it is not clear why or how this success can be transferred to the more complex biological context. We consider models for the joint…

Neurons and Cognition · Quantitative Biology 2024-12-06 Luisa Ramirez , William Bialek , Stephanie E. Palmer , David J. Schwab

The common cause principle for two random variables $A$ and $B$ is examined in the case of causal insufficiency, when their common cause $C$ is known to exist, but only the joint probability of $A$ and $B$ is observed. As a result, $C$…

Data Analysis, Statistics and Probability · Physics 2024-07-26 A. Hovhannisyan , A. E. Allahverdyan

We study the generation of a secret key of maximum rate by a pair of terminals observing correlated sources and with the means to communicate over a noiseless public com- munication channel. Our main result establishes a structural…

Information Theory · Computer Science 2016-11-17 Himanshu Tyagi

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

Shannon information was defined for characterizing the uncertainty information of classical probabilistic distributions. As an uncertainty measure it is generally believed to be positive. This holds for any information quantity from two…

Quantum Physics · Physics 2022-12-13 Ming-Xing Luo

In this paper, we take a unified approach for network information theory and prove a coding theorem, which can recover most of the achievability results in network information theory that are based on random coding. The final single-letter…

Information Theory · Computer Science 2015-05-22 Si-Hyeon Lee , Sae-Young Chung

Random factor graphs provide a powerful framework for the study of inference problems such as decoding problems or the stochastic block model. Information-theoretically the key quantity of interest is the mutual information between the…

Discrete Mathematics · Computer Science 2021-04-27 Amin Coja-Oghlan , Max Hahn-Klimroth , Philipp Loick , Noela Müller , Konstantinos Panagiotou , Matija Pasch

Wyner's soft-covering lemma is the central analysis step for achievability proofs of information theoretic security, resolvability, and channel synthesis. It can also be used for simple achievability proofs in lossy source coding. This work…

Information Theory · Computer Science 2016-05-23 Paul Cuff

In information theory, one major goal is to find useful functions that summarize the amount of information contained in the interaction of several random variables. Specifically, one can ask how the classical Shannon entropy, mutual…

Information Theory · Computer Science 2025-02-14 Leon Lang , Pierre Baudot , Rick Quax , Patrick Forré

A simple proof for the Shannon coding theorem, using only the Markov inequality, is presented. The technique is useful for didactic purposes, since it does not require many preliminaries and the information density and mutual information…

Information Theory · Computer Science 2012-05-08 Yuval Lomnitz , Meir Feder

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

The problem of how to properly quantify redundant information is an open question that has been the subject of much recent research. Redundant information refers to information about a target variable S that is common to two or more…

Information Theory · Computer Science 2017-07-14 Robin A. A. Ince

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

We explore a few common models on how correlations affect information. The main model considered is the Shannon mutual information $I(S:R_1,\cdots, R_i)$ over distributions with marginals $P_{S,R_i}$ fixed for each $i$, with the analogy in…

Information Theory · Computer Science 2024-05-27 Ching-Peng Huang

Of the various attempts to generalize information theory to multiple variables, the most widely utilized, interaction information, suffers from the problem that it is sometimes negative. Here we reconsider from first principles the general…

Information Theory · Computer Science 2010-04-16 Paul L. Williams , Randall D. Beer

We establish the rate region of an extended Gray-Wyner system for 2-DMS $(X,Y)$ with two additional decoders having complementary causal side information. This extension is interesting because in addition to the operationally significant…

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

In this paper we introduce Neural Network Coding(NNC), a data-driven approach to joint source and network coding. In NNC, the encoders at each source and intermediate node, as well as the decoder at each destination node, are neural…

Information Theory · Computer Science 2021-01-12 Litian Liu , Amit Solomon , Salman Salamatian , Muriel Medard