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We present herein a scheme by which to accurately evaluate the error exponents of a lossy data compression problem, which characterize average probabilities over a code ensemble of compression failure and success above or below a critical…

Statistical Mechanics · Physics 2007-05-23 Tadaaki Hosaka , Yoshiyuki Kabashima

This paper provides an extensive study of the behavior of the best achievable rate (and other related fundamental limits) in variable-length lossless compression. In the non-asymptotic regime, the fundamental limits of fixed-to-variable…

Information Theory · Computer Science 2012-12-13 Ioannis Kontoyiannis , Sergio Verdu

The problem of joint universal source coding and identification is considered in the setting of fixed-rate lossy coding of continuous-alphabet memoryless sources. For a wide class of bounded distortion measures, it is shown that any…

Information Theory · Computer Science 2007-07-13 Maxim Raginsky

We consider finite blocklength lossy compression of information sources whose components are independent but non-identically distributed. Crucially, Gaussian sources with memory and quadratic distortion can be cast in this form. We show…

Information Theory · Computer Science 2026-02-11 Eyyup Tasci , Victoria Kostina

Here we write in a unified fashion (using "R(P, Q, D)") the random coding exponents in channel coding and lossy source coding. We derive their explicit forms and show, that, for a given random codebook distribution Q, the channel decoding…

Information Theory · Computer Science 2017-10-31 Sergey Tridenski , Ram Zamir

Focal loss has recently gained significant popularity, particularly in tasks like object detection where it helps to address class imbalance by focusing more on hard-to-classify examples. This work proposes the focal loss as a distortion…

Information Theory · Computer Science 2025-04-29 Alex Dytso , Martina Cardone

In this paper, we revisit the discrete lossy Gray-Wyner problem. In particular, we derive its optimal second-order coding rate region, its error exponent (reliability function) and its moderate deviations constant under mild conditions on…

Information Theory · Computer Science 2017-01-05 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

We consider the lossy quantum source coding problem where the task is to compress a given quantum source below its von Neumann entropy. Inspired by the duality connections between the rate-distortion and channel coding problems in the…

Quantum Physics · Physics 2023-02-02 Touheed Anwar Atif , Mohammad Aamir Sohail , S. Sandeep Pradhan

We study the moderate-deviations (MD) setting for lossy source coding of stationary memoryless sources. More specifically, we derive fundamental compression limits of source codes whose rates are $R(D) \pm \epsilon_n$, where $R(D)$ is the…

Information Theory · Computer Science 2012-05-11 Vincent Y. F. Tan

This paper studies a variant of the rate-distortion problem motivated by task-oriented semantic communication and distributed learning systems, where $M$ correlated sources are independently encoded for a central decoder. The decoder has…

Information Theory · Computer Science 2025-01-24 Jiancheng Tang , Qianqian Yang

We propose an approach to lossy source coding, utilizing ideas from Gibbs sampling, simulated annealing, and Markov Chain Monte Carlo (MCMC). The idea is to sample a reconstruction sequence from a Boltzmann distribution associated with an…

Information Theory · Computer Science 2016-11-17 Shirin Jalali , Tsachy Weissman

The rate-distortion (RD) theory is one of the key concepts in information theory, providing theoretical limits for compression performance and guiding the source coding design, with both theoretical and practical significance. The…

Information Theory · Computer Science 2025-07-28 Shitong Wu , Sicheng Xu , Lingyi Chen , Huihui Wu , Wenyi Zhang

A general method of source coding over expansion is proposed in this paper, which enables one to reduce the problem of compressing an analog (continuous-valued source) to a set of much simpler problems, compressing discrete sources.…

Information Theory · Computer Science 2013-08-13 Hongbo Si , O. Ozan Koyluoglu , Sriram Vishwanath

We consider the problem of lossy source coding with a mismatched distortion measure. That is, we investigate what distortion guarantees can be made with respect to distortion measure $\tilde{\rho}$, for a source code designed such that it…

Information Theory · Computer Science 2008-04-07 Urs Niesen , Devavrat Shah , Gregory Wornell

This paper considers the problem of channel coding with a given (possibly suboptimal) maximum-metric decoding rule. A cost-constrained random-coding ensemble with multiple auxiliary costs is introduced, and is shown to achieve error…

Information Theory · Computer Science 2014-03-05 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

This paper considers the problem of lossy compression for the computation of a function of two correlated sources, both of which are observed at the encoder. Due to presence of observation costs, the encoder is allowed to observe only…

Information Theory · Computer Science 2013-07-22 Xi Liu , Osvaldo Simeone , Elza Erkip

Let $P = \{p(i)\}$ be a measure of strictly positive probabilities on the set of nonnegative integers. Although the countable number of inputs prevents usage of the Huffman algorithm, there are nontrivial $P$ for which known methods find a…

Information Theory · Computer Science 2007-07-13 Michael B. Baer

This paper applies error-exponent and dispersion-style analyses to derive finite-blocklength achievability bounds for low-density parity-check (LDPC) codes over the point-to-point channel (PPC) and multiple access channel (MAC). The…

Information Theory · Computer Science 2020-05-14 Yuxin Liu , Michelle Effros

The penalty incurred by imposing a finite delay constraint in lossless source coding of a memoryless source is investigated. It is well known that for the so-called block-to-variable and variable-to-variable codes, the redundancy decays at…

Information Theory · Computer Science 2016-11-17 Ofer Shayevitz , Eado Meron , Meir Feder , Ram Zamir

We present a new lossy compressor for discrete sources. For coding a source sequence $x^n$, the encoder starts by assigning a certain cost to each reconstruction sequence. It then finds the reconstruction that minimizes this cost and…

Information Theory · Computer Science 2009-01-19 Shirin Jalali , Andrea Montanari , Tsachy Weissman