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In this paper, we consider the information-theoretic characterization of the set of achievable rates and distortions in a broad class of multiterminal communication scenarios with general continuous-valued sources and channels. A framework…

Information Theory · Computer Science 2022-02-24 Farhad Shirani , S. Sandeep Pradhan

This paper investigates the general distributed lossless/lossy source coding formulated by Jana and Blahut. Their multi-letter rate-distortion region, an alternative to the region derived by Yang and Qin, is characterized by entropy…

Information Theory · Computer Science 2024-07-08 Jun Muramatsu

We recently proposed a new coding scheme for the L-channel multiple descriptions (MD) problem for general sources and distortion measures involving `Combinatorial Message Sharing' (CMS) [7] leading to a new achievable rate-distortion…

Information Theory · Computer Science 2011-06-01 Kumar Viswanatha , Emrah Akyol , Kenneth Rose

We define an algorithm that parses multidimensional arrays sequentially into mainly unrepeated but nested multidimensional sub-arrays of increasing size, and show that the resulting sub-block pointer encoder compresses almost every…

Information Theory · Computer Science 2014-08-20 Tyll Krueger , Guido Montufar , Ruedi Seiler , Rainer Siegmund-Schultze

We consider lossy source compression of a binary symmetric source using polar codes and the low-complexity successive encoding algorithm. It was recently shown by Arikan that polar codes achieve the capacity of arbitrary symmetric…

Information Theory · Computer Science 2009-03-03 Satish Babu Korada , Rudiger Urbanke

The problem of secure source coding with multiple terminals is extended by considering a remote source whose noisy measurements are the correlated random variables used for secure source reconstruction. The main additions to the problem…

Information Theory · Computer Science 2022-11-10 Onur Günlü , Rafael F. Schaefer , Holger Boche , H. Vincent Poor

In this paper, we study the asymptotic performance of Abelian group codes for the lossy source coding problem for arbitrary discrete (finite alphabet) memoryless sources as well as the channel coding problem for arbitrary discrete (finite…

Information Theory · Computer Science 2013-05-08 Aria G. Sahebi , S. Sandeep Pradhan

A popular approach to learning encoders for lossy compression is to use additive uniform noise during training as a differentiable approximation to test-time quantization. We demonstrate that a uniform noise channel can also be implemented…

Machine Learning · Statistics 2020-10-22 Eirikur Agustsson , Lucas Theis

This paper deals with the problem of universal lossless coding on a countable infinite alphabet. It focuses on some classes of sources defined by an envelope condition on the marginal distribution, namely exponentially decreasing envelope…

Information Theory · Computer Science 2011-07-07 Dominique Bontemps

Large alphabet source coding is a basic and well-studied problem in data compression. It has many applications such as compression of natural language text, speech and images. The classic perception of most commonly used methods is that a…

Information Theory · Computer Science 2016-07-26 Amichai Painsky , Saharon Rosset , Meir Feder

We extend Ziv and Lempel's model of finite-state encoders to the realm of lossy compression of individual sequences. In particular, the model of the encoder includes a finite-state reconstruction codebook followed by an information lossless…

Information Theory · Computer Science 2024-01-04 Neri Merhav

We consider a multiterminal source coding problem in which a source is estimated at a central processing unit from lossy-compressed remote observations. Each lossy-encoded observation is produced by a remote sensor which obtains a noisy…

Information Theory · Computer Science 2016-05-13 Ruiyang Song , Stefano Rini , Alon Kipnis , Andrea J. Goldsmith

A recent line of work has focused on the use of low-density generator matrix (LDGM) codes for lossy source coding. In this paper, wedevelop a generic technique for deriving lower bounds on the rate-distortion functions of binary linear…

Information Theory · Computer Science 2008-08-18 A. G. Dimakis , M. J. Wainwright , K. Ramchandran

In this paper, we use tools from rate-distortion theory to establish new upper bounds on the generalization error of statistical distributed learning algorithms. Specifically, there are $K$ clients whose individually chosen models are…

Machine Learning · Statistics 2022-11-23 Milad Sefidgaran , Romain Chor , Abdellatif Zaidi

Consider a generalized multiterminal source coding system, where $\ell\choose m$ encoders, each observing a distinct size-$m$ subset of $\ell$ ($\ell\geq 2$) zero-mean unit-variance symmetrically correlated Gaussian sources with correlation…

Information Theory · Computer Science 2017-10-16 Jun Chen , Li Xie , Yameng Chang , Jia Wang , Yizhong Wang

An encoder wishes to minimize the bit rate necessary to guarantee that a decoder is able to calculate a symbolwise function of a sequence available only at the encoder and a sequence that can be measured only at the decoder. This classical…

Information Theory · Computer Science 2012-04-19 Behzad Ahmadi , Osvaldo Simeone

In this paper the multicasting of independent parallel Gaussian sources over a binary erasure broadcasted channel is considered. Multiresolution embedded quantizer and layered joint source-channel coding schemes are used in order to serve…

Information Theory · Computer Science 2009-01-19 Ozgun Y. Bursalioglu , Maria Fresia , Giuseppe Caire , H. Vincent Poor

This paper investigates the joint source-channel coding problem of sending two correlated memoryless sources with common part over a memoryless multiple access channel (MAC). An inner bound and two outer bounds on the achievable distortion…

Information Theory · Computer Science 2016-12-13 Lei Yu , Houqiang Li , Chang Wen Chen

We propose two types of universal codes that are suited to two asymptotic regimes when the output alphabet is possibly continuous. The first class has the property that the error probability decays exponentially fast and we identify an…

Information Theory · Computer Science 2024-09-10 Masahito Hayashi

This paper presents a joint typicality framework for encoding and decoding nested linear codes for multi-user networks. This framework provides a new perspective on compute-forward within the context of discrete memoryless networks. In…

Information Theory · Computer Science 2016-07-01 Sung Hoon Lim , Chen Feng , Adriano Pastore , Bobak Nazer , Michael Gastpar
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