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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

For a Markov semigroup $P_t$ with invariant probability measure $\mu$, a constant $\ll>0$ is called a lower bound of the ultra-exponential convergence rate of $P_t$ to $\mu$, if there exists a constant $C\in (0,\infty)$ such that $$…

Probability · Mathematics 2014-10-14 Feng-Yu Wang

In this work, we address the lossy quantum-classical source coding with the quantum side-information (QC-QSI) problem. The task is to compress the classical information about a quantum source, obtained after performing a measurement while…

Information Theory · Computer Science 2025-02-18 Mohammad Aamir Sohail , Touheed Anwar Atif , S. Sandeep Pradhan

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 the first paper of this two part communication, we solved in a unified framework a variety of two terminal source coding problems with noncooperative encoders, thereby consolidating works of Shannon, Slepian-Wolf, Wyner,…

Information Theory · Computer Science 2007-07-13 Soumya Jana

We study the problem of compressing a source sequence in the presence of side-information that is related to the source via insertions, deletions and substitutions. We propose a simple algorithm to compress the source sequence when the…

Information Theory · Computer Science 2016-11-15 Nan Ma , Kannan Ramchandran , David Tse

We study the problem of source and message compression in the one-shot setting for the point-to-point and multi-party scenarios (with and without side information). We derive achievability results for these tasks in a unified manner, using…

Information Theory · Computer Science 2019-06-07 Anurag Anshu , Rahul Jain , Naqueeb Ahmad Warsi

We introduce a new extragradient iterative process, motivated and inspired by [S. H. Khan, A Picard-Mann Hybrid Iterative Process, Fixed Point Theory and Applications, doi:10.1186/1687-1812-2013-69], for finding a common element of the set…

Functional Analysis · Mathematics 2014-03-14 Ibrahim Karahan , Murat Ozdemir

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 consider a Shannon cipher system for memoryless sources, in which distortion is allowed at the legitimate decoder. The source is compressed using a rate distortion code secured by a shared key, which satisfies a constraint on the…

Information Theory · Computer Science 2016-11-17 Nir Weinberger , Neri Merhav

The problem of distributed testing against independence with variable-length coding is considered when the \emph{average} and not the \emph{maximum} communication load is constrained as in previous works. The paper characterizes the optimum…

Information Theory · Computer Science 2020-05-19 Sadaf Salehkalaibar , Michele Wigger

We present the problem of two-terminal source coding with Common Sum Reconstruction (CSR). Consider two terminals, each with access to one of two correlated sources. Both terminals want to reconstruct the sum of the two sources under some…

Information Theory · Computer Science 2022-09-26 Tharindu Adikari , Stark Draper

The solution of inverse problems in a variational setting finds best estimates of the model parameters by minimizing a cost function that penalizes the mismatch between model outputs and observations. The gradients required by the numerical…

Optimization and Control · Mathematics 2020-09-22 Ulrich Römer , Mahesh Narayanamurthi , Adrian Sandu

This paper considers the problem of variable-length coding over a discrete memoryless channel (DMC) with noiseless feedback. The paper provides a stochastic control view of the problem whose solution is analyzed via a newly proposed…

Information Theory · Computer Science 2016-11-18 Mohammad Naghshvar , Tara Javidi , Michèle Wigger

We consider the problem of zero error source coding with limited feedback when side information is present at the receiver. First, we derive an achievable rate region for arbitrary joint distributions on the source and the side information.…

Information Theory · Computer Science 2010-01-15 Mayank Bakshi , MIchelle Effros

Achievable and converse bounds for general channels and mismatched decoding are derived. The direct (achievable) bound is derived using random coding and the analysis is tight up to factor 2. The converse is given in term of the achievable…

Information Theory · Computer Science 2015-01-20 Nir Elkayam , Meir Feder

We determine the exact strong converse exponent of classical-quantum channel coding, for every rate above the Holevo capacity. Our form of the exponent is an exact analogue of Arimoto's, given as a transform of the Renyi capacities with…

Quantum Physics · Physics 2018-07-10 Milan Mosonyi , Tomohiro Ogawa

In this paper, we study the upper and the lower bounds on the joint source-channel coding error exponent with decoder side-information. The results in the paper are non-trivial extensions of the Csiszar's classical paper [5]. Unlike the…

Information Theory · Computer Science 2009-01-26 Cheng Chang

The design of communication systems dedicated to machine learning tasks is one key aspect of goal-oriented communications. In this framework, this article investigates the interplay between data reconstruction and learning from the same…

Information Theory · Computer Science 2024-04-30 Jiahui Wei , Elsa Dupraz , Philippe Mary

The functional autoregressive model is a Markov model taylored for data of functional nature. It revealed fruitful when attempting to model samples of dependent random curves and has been widely studied along the past few years. This…

Statistics Theory · Mathematics 2016-08-16 André Mas