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The second-order achievable rate region in Slepian-Wolf source coding systems is investigated. The concept of second-order achievable rates, which enables us to make a finer evaluation of achievable rates, has already been introduced and…

Information Theory · Computer Science 2017-03-28 Ryo Nomura , Te Sun Han

We consider the distributed compression of Soft Random Geometric Graphs (SRGGs) above the connectivity threshold. We establish the Slepian-Wolf rate region for the SRGG in the setting where there are a finite number of encoders compressing…

Information Theory · Computer Science 2026-05-07 Oliver Baker , Carl P. Dettmann

We analyze the performance of a linear code used for a data compression of Slepian-Wolf type. In our framework, two correlated data are separately compressed into codewords employing Gallager-type codes and casted into a communication…

Disordered Systems and Neural Networks · Physics 2007-05-23 Tatsuto Murayama

A method to construct nonasymmetric distributed source coding (DSC) scheme using polar codes which can achieve any point on the dominant face of the Slepian-Wolf (SW) rate region for sources with uniform marginals is considered. In addition…

Information Theory · Computer Science 2012-08-16 Saygun Onay

In this paper, we analyze the asymptotics of the normalized remaining uncertainty of a source when a compressed or hashed version of it and correlated side-information is observed. For this system, commonly known as Slepian-Wolf source…

Information Theory · Computer Science 2016-06-01 Vincent Y. F. Tan , Masahito Hayashi

Motivated by streaming multi-view video coding and wireless sensor networks, we consider the problem of blockwise streaming compression of a pair of correlated sources, which we term streaming Slepian-Wolf coding. We study the moderate…

Information Theory · Computer Science 2017-09-21 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

This work studies point-to-point, multiple access, and random access lossless source coding in the finite-blocklength regime. In each scenario, a random coding technique is developed and used to analyze third-order coding performance.…

Information Theory · Computer Science 2020-10-13 Shuqing Chen , Michelle Effros , Victoria Kostina

Let $X_1, ..., X_m$ be a set of $m$ statistically dependent sources over the common alphabet $\mathbb{F}_q$, that are linearly independent when considered as functions over the sample space. We consider a distributed function computation…

Information Theory · Computer Science 2016-11-17 V. Lalitha , N. Prakash , K. Vinodh , P. Vijay Kumar , S. Sandeep Pradhan

This paper investigates a lossy source coding problem in which two decoders can access their side-information respectively. The correlated sources are a product of two component correlated sources, and we exclusively investigate the case…

Information Theory · Computer Science 2013-05-29 Shun Watanabe

Data compression is a well-studied (and well-solved) problem in the setup of long coding blocks. But important emerging applications need to compress data to memory words of small fixed widths. This new setup is the subject of this paper.…

Information Theory · Computer Science 2017-01-12 Ori Rottenstreich , Yuval Cassuto

Practical constructions of lossless distributed source codes (for the Slepian-Wolf problem) have been the subject of much investigation in the past decade. In particular, near-capacity achieving code designs based on LDPC codes have been…

Information Theory · Computer Science 2011-06-15 Shizheng Li , Aditya Ramamoorthy

The problem of computing functions of values at the nodes in a network in a totally distributed manner, where nodes do not have unique identities and make decisions based only on local information, has applications in sensor, peer-to-peer,…

Networking and Internet Architecture · Computer Science 2007-05-23 Damon Mosk-Aoyama , Devavrat Shah

Distributed functional scalar quantization (DFSQ) theory provides optimality conditions and predicts performance of data acquisition systems in which a computation on acquired data is desired. We address two limitations of previous works:…

Information Theory · Computer Science 2015-03-24 John Z. Sun , Vinith Misra , Vivek K Goyal

We study the limits of communication efficiency for function computation in collocated networks within the framework of multi-terminal block source coding theory. With the goal of computing a desired function of sources at a sink, nodes…

Information Theory · Computer Science 2016-11-17 Nan Ma , Prakash Ishwar , Piyush Gupta

We consider a problem of coding for computing, where the decoder wishes to estimate a function of its local message and the source message at the encoder within a given distortion. We show that the rate-distortion function can be…

Information Theory · Computer Science 2022-05-18 Deheng Yuan , Tao Guo , Bo Bai , Wei Han

Consider the problem where a statistician in a two-node system receives rate-limited information from a transmitter about marginal observations of a memoryless process generated from two possible distributions. Using its own observations,…

Information Theory · Computer Science 2017-03-02 Gil Katz , Pablo Piantanida , Mérouane Debbah

For memoryless sources, delayed side information at the decoder does not improve the rate-distortion function. However, this is not the case for more general sources with memory, as demonstrated by a number of works focusing on the special…

Information Theory · Computer Science 2012-07-19 Osvaldo Simeone , Haim H. Permuter

The recently proposed set-up of source coding with a side information "vending machine" allows the decoder to select actions in order to control the quality of the side information. The actions can depend on the message received from the…

Information Theory · Computer Science 2013-01-08 Osvaldo Simeone

In this paper, we consider a class of multiterminal source coding problems, each subject to distortion constraints computed using a specific, entropy-based, distortion measure. We provide the achievable rate distortion region for two cases…

Information Theory · Computer Science 2011-06-02 Thomas Courtade , Richard Wesel

By selecting different filter functions, spectral algorithms can generate various regularization methods to solve statistical inverse problems within the learning-from-samples framework. This paper combines distributed spectral algorithms…

Machine Learning · Statistics 2025-02-18 Jiading Liu , Lei Shi