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This paper establishes the rate region for a class of source coding function computation setups where sources of information are available at the nodes of a tree and where a function of these sources must be computed at the root. The rate…

Information Theory · Computer Science 2015-04-08 Milad Sefidgaran , Aslan Tchamkerten

Inspired by mobile satellite communication systems and the important and prevalent applications of computational tasks, we consider a distributed source coding model for compressing vector-linear functions, which consists of multiple…

Information Theory · Computer Science 2025-08-06 Xuan Guang , Xiufang Sun , Ruze Zhang

The optimal causal coding of a partially observed Markov process is studied, where the cost to be minimized is a bounded, non-negative, additive, measurable single-letter function of the source and the receiver output. A structural result…

Information Theory · Computer Science 2012-08-24 Serdar Yüksel

We study finite-length bounds for source coding with side information for Markov sources and channel coding for channels with conditional Markovian additive noise. For this purpose, we propose two criteria for finite-length bounds. One is…

Information Theory · Computer Science 2017-01-10 Masahito Hayashi , Shun Watanabe

In this paper, we consider different aspects of the network functional compression problem where computation of a function (or, some functions) of sources located at certain nodes in a network is desired at receiver(s). The rate region of…

Information Theory · Computer Science 2010-12-01 Soheil Feizi , Muriel Medard

Specifying a computational problem requires fixing encodings for input and output: encoding graphs as adjacency matrices, characters as integers, integers as bit strings, and vice versa. For such discrete data, the actual encoding is…

Logic · Mathematics 2021-08-25 Donghyun Lim , Martin Ziegler

In this paper we consider point-to-point and distributed source coding problems where the receiver is only interested in a function of the data sent by the source encoder(s), while knowledge of the function remains unknown to the…

Information Theory · Computer Science 2018-11-27 Sourya Basu , Lav R. Varshney

Using the concept of discrete noiseless channels, it was shown by Shannon in A Mathematical Theory of Communication that the ultimate performance of an encoder for a constrained system is limited by the combinatorial capacity of the system…

Information Theory · Computer Science 2008-09-09 Georg Böcherer , Valdemar Cardoso da Rocha , Cecilio Pimentel

We consider the problem of coded distributed computing where a large linear computational job, such as a matrix multiplication, is divided into $k$ smaller tasks, encoded using an $(n,k)$ linear code, and performed over $n$ distributed…

Information Theory · Computer Science 2019-06-25 Mohammad Vahid Jamali , Mahdi Soleymani , Hessam Mahdavifar

We consider the problem of coded distributed computing where a large linear computational job, such as a matrix multiplication, is divided into $k$ smaller tasks, encoded using an $(n,k)$ linear code, and performed over $n$ distributed…

Information Theory · Computer Science 2021-10-06 Mahdi Soleymani , Mohammad Vahid Jamali , Hessam Mahdavifar

We study joint source-channel coding over Markov channels through the empirical coordination framework. More specifically, we aim at determining the empirical distributions of source and channel symbols that can be induced by a coding…

Information Theory · Computer Science 2026-05-06 Mengyuan Zhao , Maël Le Treust , Tobias J. Oechtering

In this paper we consider an interacting two-agent sequential decision-making problem consisting of a Markov source process, a causal encoder with feedback, and a causal decoder. Motivated by a desire to foster links between control and…

Information Theory · Computer Science 2015-03-18 Siva Gorantla , Todd Coleman

This paper introduces an objective function that seeks to minimise the average total number of bits required to encode the joint state of all of the layers of a Markov source. This type of encoder may be applied to the problem of optimising…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Stephen Luttrell

The problem of computing a linear combination of sources over a multiple access channel is studied. Inner and outer bounds on the optimal tradeoff between the communication rates are established when encoding is restricted to random…

Information Theory · Computer Science 2018-10-30 Pinar Sen , Sung Hoon Lim , Young-Han Kim

We consider the problem of information aggregation in sensor networks, where one is interested in computing a function of the sensor measurements. We allow for block processing and study in-network function computation in directed graphs…

Information Theory · Computer Science 2015-03-19 Hemant Kowshik , P. R. Kumar

Inspired by prior work by Tian and by Cao and Xu, this paper presents an efficient computer-aided framework to characterize the fundamental limits of coded caching systems under the constraint of linear coding. The proposed framework…

Information Theory · Computer Science 2025-11-26 Niccolò Brembilla , Yinbin Ma , Pietro Belotti , Federico Malucelli , Daniela Tuninetti

Our understanding of information in systems has been based on the foundation of memoryless processes. Extensions to stable Markov and auto-regressive processes are classical. Berger proved a source coding theorem for the marginally unstable…

Information Theory · Computer Science 2007-12-06 Anant Sahai , Sanjoy Mitter

A real time coding system with lookahead consists of a memoryless source, a memoryless channel, an encoder, which encodes the source symbols sequentially with knowledge of future source symbols upto a fixed finite lookahead, d, with or…

Information Theory · Computer Science 2011-05-31 Himanshu Asnani , Tsachy Weissman

We study the use of linear codes for network computing in single-receiver networks with various classes of target functions of the source messages. Such classes include reducible, injective, semi-injective, and linear target functions over…

Information Theory · Computer Science 2011-05-10 Rathinakumar Appuswamy , Massimo Franceschetti , Nikhil Karamchandani , Kenneth Zeger

This work investigates functional source coding problems with maximal distortion, motivated by approximate function computation in many modern applications. The maximal distortion treats imprecise reconstruction of a function value as good…

Information Theory · Computer Science 2022-12-29 Sourya Basu , Daewon Seo , Lav R. Varshney
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