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In the classical source coding problem, the compressed source is reconstructed at the decoder with respect to some distortion metric. Motivated by settings in which we are interested in more than simply reconstructing the compressed source,…

Information Theory · Computer Science 2023-10-03 Oğuzhan Kubilay Ülger , Elza Erkip

This paper investigates the problem of variable-length lossy source coding allowing a positive excess distortion probability and an overflow probability of codeword lengths. Novel one-shot achievability and converse bounds of the optimal…

Information Theory · Computer Science 2018-12-17 Shota Saito , Hideki Yagi , Toshiyasu Matsushima

A distributed lossy compression network with $L$ encoders and a decoder is considered. Each encoder observes a source and sends a compressed version to the decoder. The decoder produces a joint reconstruction of target signals with the mean…

Information Theory · Computer Science 2022-06-06 Siyao Zhou , Sadaf Salehkalaibar , Jingjing Qian , Jun Chen , Wuxian Shi , Yiqun Ge , Wen Tong

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

In this work we investigate the behavior of the minimal rate needed in order to guarantee a given probability that the distortion exceeds a prescribed threshold, at some fixed finite quantization block length. We show that the excess coding…

Information Theory · Computer Science 2011-02-15 Amir Ingber , Yuval Kochman

The distortion-rate function of output-constrained lossy source coding with limited common randomness is analyzed for the special case of squared error distortion measure. An explicit expression is obtained when both source and…

Information Theory · Computer Science 2024-03-25 Li Xie , Liangyan Li , Jun Chen , Zhongshan Zhang

Consider a lossy compression system with $\ell$ distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under…

Information Theory · Computer Science 2018-07-19 Yizhong Wang , Li Xie , Xuan Zhang , Jun Chen

For a number of lossy source coding problems it is shown that even if the usual single-letter sum-rate-distortion expressions may become invalid for non-infinite distortion functions, they can be approached, to any desired accuracy, via the…

Information Theory · Computer Science 2014-08-05 Prakash Ishwar

We study the problem of efficient compression of a stochastic source of probability distributions. It can be viewed as a generalization of Shannon's source coding problem. It has relation to the theory of common randomness, as well as to…

Quantum Physics · Physics 2016-09-08 Andreas Winter

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

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

This paper studies a Shannon-theoretic version of the generalized distribution preserving quantization problem where a stationary and memoryless source is encoded subject to a distortion constraint and the additional requirement that the…

Information Theory · Computer Science 2015-07-10 Naci Saldi , Tamás Linder , Serdar Yüksel

We consider the problem of source compression under three different scenarios in the one-shot (non- asymptotic) regime. To be specific, we prove one-shot achievability and converse bounds on the coding rates for distributed source coding,…

Information Theory · Computer Science 2015-12-11 Naqueeb Ahmad Warsi

In this work we investigate the behavior of the distortion threshold that can be guaranteed in joint source-channel coding, to within a prescribed excess-distortion probability. We show that the gap between this threshold and the optimal…

Information Theory · Computer Science 2011-12-08 Da Wang , Amir Ingber , Yuval Kochman

We provide a framework for one-shot quantum rate distortion coding, in which the goal is to determine the minimum number of qubits required to compress quantum information as a function of the probability that the distortion incurred upon…

Quantum Physics · Physics 2013-12-09 Nilanjana Datta , Joseph M. Renes , Renato Renner , Mark M. Wilde

We introduce a universal quantization scheme based on random coding, and we analyze its performance. This scheme consists of a source-independent random codebook (typically_mismatched_ to the source distribution), followed by optimal…

Information Theory · Computer Science 2007-07-13 Ioannis Kontoyiannis , Rami Zamir

We examine the coordinated and universal rate-efficient sampling of a subset of correlated discrete memoryless sources followed by lossy compression of the sampled sources. The goal is to reconstruct a predesignated subset of sources within…

Information Theory · Computer Science 2017-06-23 Vinay Praneeth Boda , Prakash Narayan

We consider a novel variant of $d$-semifaithful lossy coding in which the distortion measure is revealed only to the encoder and only at run-time, as well as an extension of it in which the distortion constraint $d$ is also revealed at…

Information Theory · Computer Science 2022-10-05 Adeel Mahmood , Aaron B. Wagner

This paper shows new general nonasymptotic achievability and converse bounds and performs their dispersion analysis for the lossy compression problem in which the compressor observes the source through a noisy channel. While this problem is…

Information Theory · Computer Science 2016-09-19 Victoria Kostina , Sergio Verdú

This paper considers lossy source coding of $n$-dimensional memoryless sources and shows an explicit approximation to the minimum source coding rate required to sustain the probability of exceeding distortion $d$ no greater than $\epsilon$,…

Information Theory · Computer Science 2017-02-28 Victoria Kostina
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