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We study lossy source coding under a distortion measure defined by the negative log-likelihood induced by a prescribed conditional distribution $P_{X|U}$. This \emph{log-likelihood distortion} models compression settings in which the…

Information Theory · Computer Science 2026-01-26 Anuj Kumar Yadav , Dan Song , Yanina Shkel , Ayfer Özgür

We study a new class of codes for lossy compression with the squared-error distortion criterion, designed using the statistical framework of high-dimensional linear regression. Codewords are linear combinations of subsets of columns of a…

Information Theory · Computer Science 2015-12-21 Ramji Venkataramanan , Antony Joseph , Sekhar Tatikonda

The source-coding problem with side information at the decoder is studied subject to a constraint that the encoder---to whom the side information is unavailable---be able to compute the decoder's reconstruction sequence to within some…

Information Theory · Computer Science 2016-11-15 Amos Lapidoth , Andreas Malär , Michèle Wigger

The amount of information lost in sub-Nyquist sampling of a continuous-time Gaussian stationary process is quantified. We consider a combined source coding and sub-Nyquist reconstruction problem in which the input to the encoder is a noisy…

Information Theory · Computer Science 2016-01-26 Alon Kipnis , Andrea J. Goldsmith , Yonina C. Eldar , Tsachy Weissman

A lossy source code $\mathcal{C}$ with rate $R$ for a discrete memoryless source $S$ is called subset-universal if for every $0<R'< R$, almost every subset of $2^{nR'}$ of its codewords achieves average distortion close to the source's…

Information Theory · Computer Science 2015-03-13 Or Ordentlich , Ofer Shayevitz

We consider the rate-distortion function for lossy source compression, as well as the channel capacity for error correction, through the lens of distributional robustness. We assume that the distribution of the source or of the additive…

Information Theory · Computer Science 2024-05-14 Vikrant Malik , Taylan Kargin , Victoria Kostina , Babak Hassibi

In lossy compression, Wang et al. [1] recently introduced the rate-distortion-perception-classification function, which supports multi-task learning by jointly optimizing perceptual quality, classification accuracy, and reconstruction…

Information Theory · Computer Science 2025-04-23 Nam Nguyen , Thuan Nguyen , Thinh Nguyen , Bella Bose

We propose a universal ensemble for random selection of rate-distortion codes, which is asymptotically optimal in a sample-wise sense. According to this ensemble, each reproduction vector, $\hbx$, is selected independently at random under…

Information Theory · Computer Science 2022-12-26 Neri Merhav

We investigate distributed source coding of two correlated sources X and Y where messages are passed to a decoder in a cascade fashion. The encoder of X sends a message at rate R_1 to the encoder of Y. The encoder of Y then sends a message…

Information Theory · Computer Science 2009-05-13 Paul Cuff , Han-I Su , Abbas El Gamal

Past works on remote lossy source coding studied the rate under average distortion and the error exponent of excess distortion probability. In this work, we look into how fast the excess distortion probability converges to 1 at small rates,…

Information Theory · Computer Science 2025-04-24 Han Wu , Hamdi Joudeh

We study task-oriented lossy compression through the lens of rate-distortion-classification (RDC) representations. The source is Bernoulli, the distortion measure is Hamming, and the binary classification variable is coupled to the source…

Information Theory · Computer Science 2026-05-19 Nam Nguyen , Thinh Nguyen , Bella Bose

Locally decodable channel codes form a special class of error-correcting codes with the property that the decoder is able to reconstruct any bit of the input message from querying only a few bits of a noisy codeword. It is well known that…

Information Theory · Computer Science 2013-08-28 Ali Makhdoumi , Shao-Lun Huang , Muriel Medard , Yury Polyanskiy

We consider a rate-distortion version of the quantum state redistribution task, where the error of the decoded state is judged via an additive distortion measure; it thus constitutes a quantum generalisation of the classical Wyner-Ziv…

Quantum Physics · Physics 2025-04-11 Zahra Baghali Khanian , Andreas Winter

We consider the problem of estimating a Gaussian random walk from a lossy compression of its decimated version. Hence, the encoder operates on the decimated random walk, and the decoder estimates the original random walk from its encoded…

Signal Processing · Electrical Eng. & Systems 2018-02-28 Georgia Murray , Alon Kipnis , Andrea J. Goldsmith

In this paper, we investigate the problem of distributionally robust source coding, i.e., source coding under uncertainty in the source distribution, discussing both the coding and computational aspects of the problem. We propose two…

Information Theory · Computer Science 2025-07-24 Giuseppe Serra , Photios A. Stavrou , Marios Kountouris

We consider the distributed source coding system for $L$ correlated Gaussian observations $Y_i, i=1,2, ..., L$. Let $X_i,i=1,2, ..., L$ be $L$ correlated Gaussian random variables and $N_i,$ $i=1,2,... L$ be independent additive Gaussian…

Information Theory · Computer Science 2009-08-09 Yasutada Oohama

We present a unified one-shot coding framework designed for the communication and compression of messages among multiple nodes across a general acyclic noisy network. Our setting can be seen as a one-shot version of the acyclic discrete…

Information Theory · Computer Science 2025-08-19 Yanxiao Liu , Cheuk Ting Li

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

Variable-length compression without prefix-free constraints and with side-information available at both encoder and decoder is considered. Instead of requiring the code to be error-free, we allow for it to have a non-vanishing error…

Information Theory · Computer Science 2020-08-24 Yuta Sakai , Vincent Y. F. Tan

We propose the notion of a sample distortion (SD) function for independent and identically distributed (i.i.d) compressive distributions to fundamentally quantify the achievable reconstruction performance of compressed sensing for certain…

Computer Vision and Pattern Recognition · Computer Science 2015-06-15 Chunli Guo , Mike E. Davies