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Rate-distortion-perception theory generalizes Shannon's rate-distortion theory by introducing a constraint on the perceptual quality of the output. The perception constraint complements the conventional distortion constraint and aims to…

Information Theory · Computer Science 2022-04-14 Jun Chen , Lei Yu , Jia Wang , Wuxian Shi , Yiqun Ge , Wen Tong

This paper is concerned with a rate-distortion theory for sequences of i.i.d. random variables with general distribution supported on general sets including manifolds and fractal sets. Manifold structures are prevalent in data science,…

Information Theory · Computer Science 2018-04-25 Erwin Riegler , Günther Koliander , Helmut Bölcskei

In this paper the relation between nonanticipative rate distortion function (RDF) and Bayesian filtering theory is further investigated on general Polish spaces. The relation is established via an optimization on the space of conditional…

Information Theory · Computer Science 2014-01-21 Photios A. Stavrou , Charalambos D. Charalambous

Rate distortion theory treats the problem of encoding a source with minimum codebook size while at the same time allowing for a certain amount of errors in the reconstruction measured by a fidelity criterion and distortion level. Similar to…

Information Theory · Computer Science 2025-11-13 Jonathan E. W. Huffmann , Holger Boche

The Shannon lower bound is one of the few lower bounds on the rate-distortion function that holds for a large class of sources. In this paper, it is demonstrated that its gap to the rate-distortion function vanishes as the allowed…

Information Theory · Computer Science 2016-11-17 Tobias Koch

In the successive refinement problem, a fixed-length sequence emitted from an information source is encoded into two codewords by two encoders in order to give two reconstructions of the sequence. One of two reconstructions is obtained by…

Information Theory · Computer Science 2018-12-26 Tetsunao Matsuta , Tomohiko Uyematsu

In successive refinement of information, the decoder refines its representation of the source progressively as it receives more encoded bits. The rate-distortion region of successive refinement describes the minimum rates required to attain…

Information Theory · Computer Science 2018-11-22 Victoria Kostina , Ertem Tuncel

We establish a theory of quantum-to-classical rate distortion coding. In this setting, a sender Alice has many copies of a quantum information source. Her goal is to transmit classical information about the source, obtained by performing a…

Quantum Physics · Physics 2013-04-05 Nilanjana Datta , Min-Hsiu Hsieh , Mark M. Wilde , Andreas Winter

Transformers achieve superior performance on many tasks, but impose heavy compute and memory requirements during inference. This inference can be made more efficient by partitioning the process across multiple devices, which, in turn,…

Machine Learning · Computer Science 2026-04-21 Anderson de Andrade , Alon Harell , Ivan V. Bajić

We derive quantum counterparts of two key theorems of classical information theory, namely, the rate distortion theorem and the source-channel separation theorem. The rate-distortion theorem gives the ultimate limits on lossy data…

Quantum Physics · Physics 2012-12-21 Nilanjana Datta , Min-Hsiu Hsieh , Mark M. Wilde

We consider a remote source coding problem subject to a {distortion function}. Contrary to the use of the classical separable distortion criterion, herein we consider the more general, $f$-separable distortion measure and study its…

Information Theory · Computer Science 2023-05-19 Photios A. Stavrou , Yanina Shkel , Marios Kountouris

Consider a distributed coding for computing problem with constant decoding locality, i.e., with a vanishing error probability, any single sample of the function can be approximately recovered by probing only constant number of compressed…

Information Theory · Computer Science 2024-03-01 Deheng Yuan , Tao Guo , Zhongyi Huang , Shi Jin

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

We formulate quantum rate-distortion theory in the most general setting where classical side information is included in the tradeoff. Using a natural distortion measure based on entanglement fidelity and specializing to the case of an…

Quantum Physics · Physics 2009-09-25 Igor Devetak , Toby Berger

We investigate the upper and lower bounds on the quantization distortions for independent and identically distributed sources in the finite block-length regime. Based on the convex optimization framework of the rate-distortion theory, we…

Information Theory · Computer Science 2013-06-21 Chen Gong , Xiaodong Wang

We examine the structure of families of distortion balls from the perspective of Kolmogorov complexity. Special attention is paid to the canonical rate-distortion function of a source word which returns the minimal Kolmogorov complexity of…

Information Theory · Computer Science 2009-11-26 Nikolai K. Vereshchagin , Paul M. B. Vitanyi

We approach index coding as a special case of rate-distortion with multiple receivers, each with some side information about the source. Specifically, using techniques developed for the rate-distortion problem, we provide two upper bounds…

Information Theory · Computer Science 2015-07-28 Sinem Unal , Aaron B. Wagner

I introduce rate-distortion theory for quantum coding, and derive a lower bound, involving the coherent information, on the rate at which qubits must be used to encode a quantum source with a given maximum level of distortion per source…

Quantum Physics · Physics 2007-05-23 Howard Barnum

This paper studies fixed-rate randomized vector quantization under the constraint that the quantizer's output has a given fixed probability distribution. A general representation of randomized quantizers that includes the common models in…

Information Theory · Computer Science 2016-11-15 Naci Saldi , Tamás Linder , Serdar Yüksel

We study the compression of data in the case where the useful information is contained in a set rather than a vector, i.e., the ordering of the data points is irrelevant and the number of data points is unknown. Our analysis is based on…

Information Theory · Computer Science 2018-05-23 Günther Koliander , Dominic Schuhmacher , Franz Hlawatsch