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We study distributed binary hypothesis testing with a single sensor and two remote decision centers that are also equipped with local sensors. The communication between the sensor and the two decision centers takes place over three links: a…

Information Theory · Computer Science 2022-02-07 Mustapha Hamad , Mireille Sarkiss , Michèle Wigger

Privacy-preserving average consensus aims to guarantee the privacy of initial states and asymptotic consensus on the exact average of the initial value. In existing work, it is achieved by adding and subtracting variance decaying and…

Systems and Control · Computer Science 2017-02-10 Jianping He , Lin Cai , Chengcheng Zhao , Peng Cheng , Xinping Guan

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

In this paper, we derive information-theoretic performance limits for secure and reliable communications over the general two-user discrete memoryless broadcast channel with side-information at the transmitter. The sender wishes to…

Information Theory · Computer Science 2011-09-27 K. G. Nagananda , Chandra R Murthy , Shalinee Kishore

Inspired by Aumann's agreement theorem, Scott Aaronson studied the amount of communication necessary for two Bayesian experts to approximately agree on the expectation of a random variable. Aaronson showed that, remarkably, the number of…

Computer Science and Game Theory · Computer Science 2021-11-08 Rafael Frongillo , Eric Neyman , Bo Waggoner

We study the problem of rate-distortion-equivocation with side-information only available at the decoder when an independent private random key is shared between the sender and the receiver. The sender compresses the sequence, and the…

Information Theory · Computer Science 2022-01-25 Hamid Ghourchian , Photios A. Stavrou , Tobias J. Oechtering , Mikael Skoglund

We study the problem of discrete distribution testing in the two-party setting. For example, in the standard closeness testing problem, Alice and Bob each have $t$ samples from, respectively, distributions $a$ and $b$ over $[n]$, and they…

Data Structures and Algorithms · Computer Science 2018-11-12 Alexandr Andoni , Tal Malkin , Negev Shekel Nosatzki

We analyse the common information problem for the generalised Gray-Wyner problem. We aim to explore the problem and solution in relation to the non-orthogonality among the source decoders' components. We consider a simple networked control…

Information Theory · Computer Science 2022-01-07 Makan Zamanipour

The problem of secure multiterminal source coding with side information at the eavesdropper is investigated. This scenario consists of a main encoder (referred to as Alice) that wishes to compress a single source but simultaneously…

Information Theory · Computer Science 2013-11-11 Joffrey Villard , Pablo Piantanida

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

The question of how much communication is required between collaborating parties to compute a function of their data is of fundamental importance in the fields of theoretical computer science and information theory. In this work, the focus…

Information Theory · Computer Science 2016-02-09 Shijin Rajakrishnan , Sundara Rajan S , Vinod Prabhakaran

The entropy of a pair of random variables is commonly depicted using a Venn diagram. This representation is potentially misleading, however, since the multivariate mutual information can be negative. This paper presents new measures of…

Information Theory · Computer Science 2020-04-22 Conor Finn , Joseph T. Lizier

In this work, lossy distributed compression of pairs of correlated sources is considered. Conventionally, Shannon's random coding arguments -- using randomly generated unstructured codebooks whose blocklength is taken to be asymptotically…

Information Theory · Computer Science 2020-10-21 Farhad Shirani , S. Sandeep Pradhan

Mutual information is the reciprocal information that is common to or shared by two or more parties. Quantum mutual information for bipartite quantum systems is non-negative, and bears the interpretation of total correlation between the two…

Quantum Physics · Physics 2017-08-02 Asutosh Kumar

We study the problem of privacy preservation in data sharing, where $S$ is a sensitive variable to be protected and $X$ is a non-sensitive useful variable correlated with $S$. Variable $X$ is randomized into variable $Y$, which will be…

Information Theory · Computer Science 2020-10-20 Parastoo Sadeghi , Ni Ding , Thierry Rakotoarivelo

Shared information is a measure of mutual dependence among multiple jointly distributed random variables with finite alphabets. For a Markov chain on a tree with a given joint distribution, we give a new proof of an explicit…

Information Theory · Computer Science 2024-01-23 Sagnik Bhattacharya , Prakash Narayan

Multiple players are each given one independent sample, about which they can only provide limited information to a central referee. Each player is allowed to describe its observed sample to the referee using a channel from a family of…

Data Structures and Algorithms · Computer Science 2020-10-02 Jayadev Acharya , Clément L. Canonne , Himanshu Tyagi

This paper proposes a distributed algorithm for average consensus in a multi-agent system under a fixed bidirectional communication topology, in the presence of malicious agents (nodes) that may try to influence the average consensus…

Multiagent Systems · Computer Science 2023-09-06 Christoforos N. Hadjicostis , Alejandro D. Dominguez-Garcia

The rapid development in data collecting devices and computation platforms produces an emerging number of agents, each equipped with a unique data modality over a particular population of subjects. While the predictive performance of an…

Machine Learning · Computer Science 2020-10-22 Jiaying Zhou , Xun Xian , Na Li , Jie Ding

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

Quantum Physics · Physics 2019-08-27 Christoph Hirche , David Reeb
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