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Recently, a number of authors have proposed decoding schemes for Reed-Solomon (RS) codes based on multiple trials of a simple RS decoding algorithm. In this paper, we present a rate-distortion (R-D) approach to analyze these…

Information Theory · Computer Science 2009-08-21 Phong S. Nguyen , Henry D. Pfister , Krishna R. Narayanan

We consider causal, low-latency, sequential lossy compression, with mean squared-error (MSE) as the distortion loss, and a perception loss function (PLF) to enhance the realism of reconstructions. As the main contribution, we propose and…

Machine Learning · Computer Science 2025-02-18 Sadaf Salehkalaibar , Buu Phan , Likun Cai , Joao Atz Dick , Wei Yu , Jun Chen , Ashish Khisti

In this work, we introduce a new procedure for applying Restricted Boltzmann Machines (RBMs) to missing data inference tasks, based on linearization of the effective energy function governing the distribution of observations. We compare the…

Machine Learning · Computer Science 2019-10-22 Chris Cannella , Jie Ding , Mohammadreza Soltani , Vahid Tarokh

We establish the first information-theoretic limits for multimodal retrieval. Casting ranking as lossy source coding, we derive a single-letter rate-distortion function $R(D)$ for reciprocal-rank distortion and prove a converse bound that…

Information Theory · Computer Science 2025-09-16 Thomas Y. Chen

We prove achievability of the recently characterized quadratic Gaussian rate-distortion function (RDF) subject to the constraint that the distortion is uncorrelated to the source. This result is based on shaped dithered lattice quantization…

Information Theory · Computer Science 2008-07-24 Milan S. Derpich , Jan Ostergaard , Daniel E. Quevedo

In this paper, we study communication efficient distributed algorithms for distributionally robust federated learning via periodic averaging with adaptive sampling. In contrast to standard empirical risk minimization, due to the minimax…

Machine Learning · Computer Science 2021-02-26 Yuyang Deng , Mohammad Mahdi Kamani , Mehrdad Mahdavi

In the theory of lossy compression, the rate-distortion (R-D) function $R(D)$ describes how much a data source can be compressed (in bit-rate) at any given level of fidelity (distortion). Obtaining $R(D)$ for a given data source establishes…

Information Theory · Computer Science 2023-10-31 Yibo Yang , Stephan Eckstein , Marcel Nutz , Stephan Mandt

In this paper we study the problem of characterizing and computing the nonanticipative rate distortion function (NRDF) for partially observable multivariate Gauss-Markov processes with hard mean squared error (MSE) distortion constraints.…

Information Theory · Computer Science 2021-10-22 Photios A. Stavrou , Mikael Skoglund

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

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

The self-random number generation (SRNG) problem is considered for general setting. In the literature, the optimum SRNG rate with respect to the variational distance has been discussed. In this paper, we first try to characterize the…

Information Theory · Computer Science 2024-02-01 Ryo Nomura

The quantum rate-distortion function plays a fundamental role in quantum information theory, however there is currently no practical algorithm which can efficiently compute this function to high accuracy for moderate channel dimensions. In…

Quantum Physics · Physics 2024-04-10 Kerry He , James Saunderson , Hamza Fawzi

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

The relation between nonanticipative Rate Distortion Function (RDF) and filtering theory is discussed on abstract spaces. The relation is established by imposing a realizability constraint on the reconstruction conditional distribution of…

Information Theory · Computer Science 2016-11-15 Charalambos D. Charalambous , Photios A. Stavrou , Nasir U. Ahmed

The Perception-Distortion tradeoff (PD-tradeoff) theory suggests that face restoration algorithms must balance perceptual quality and fidelity. To achieve minimal distortion while maintaining perfect perceptual quality, Posterior-Mean…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xin Luo , Menglin Zhang , Yunwei Lan , Tianyu Zhang , Rui Li , Chang Liu , Dong Liu

Recent efforts in neural compression have focused on the rate-distortion-perception (RDP) tradeoff, where the perception constraint ensures the source and reconstruction distributions are close in terms of a statistical divergence.…

Information Theory · Computer Science 2025-05-21 Eric Lei , Hamed Hassani , Shirin Saeedi Bidokhti

This paper studies the minimum achievable source coding rate as a function of blocklength $n$ and probability $\epsilon$ that the distortion exceeds a given level $d$. Tight general achievability and converse bounds are derived that hold at…

Information Theory · Computer Science 2016-11-15 Victoria Kostina , Sergio Verdú

In this paper we consider the rate distortion problem of discrete-time, ergodic, and stationary sources with feed forward at the receiver. We derive a sequence of achievable and computable rates that converge to the feed-forward rate…

Information Theory · Computer Science 2011-06-07 Iddo Naiss , Haim Permuter

We revisit the Gray-Wyner lossy source coding problem and derive the first-order asymptotic optimal rate-distortion-perception region when additional perception constraints are imposed on reproduced source sequences. The optimal trade-off…

Information Theory · Computer Science 2026-01-19 Yu Yang , Yingxin Zhang , Weijie Yuan , Lin Zhou

With the increasing number of images and videos consumed by computer vision algorithms, compression methods are evolving to consider both perceptual quality and performance in downstream tasks. Traditional codecs can tackle this problem by…

Image and Video Processing · Electrical Eng. & Systems 2024-08-14 Samuel Fernández Menduiña , Eduardo Pavez , Antonio Ortega