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We present a general theory of the corrections to the asymptotic behaviour of the Renyi entropies which measure the entanglement of an interval A of length L with the rest of an infinite one-dimensional system, in the case when this is…

Statistical Mechanics · Physics 2011-02-16 John Cardy , Pasquale Calabrese

Text compression schemes and compact data structures usually combine sophisticated probability models with basic coding methods whose average codeword length closely match the entropy of known distributions. In the frequent case where basic…

Information Theory · Computer Science 2019-10-02 N. Jesper Larsson

We study finite-length bounds for source coding with side information for Markov sources and channel coding for channels with conditional Markovian additive noise. For this purpose, we propose two criteria for finite-length bounds. One is…

Information Theory · Computer Science 2017-01-10 Masahito Hayashi , Shun Watanabe

We present an upper bound on the error probability achievable using variable-length stop feedback codes, for a fixed size of the information payload and a given constraint on the maximum latency and the average service time. Differently…

Information Theory · Computer Science 2020-02-20 Johan Östman , Rahul Devassy , Giuseppe Durisi , Erik G. Ström

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

Variable-to-variable length (VV) codes are a class of lossless source coding. As their name implies, VV codes encode a variable-length sequence of source symbols into a variable-length codeword. This paper will give a complete proof of an…

Information Theory · Computer Science 2023-09-13 Wei Yan , Yunghsiang S. Han

In this paper, we consider a class of multiterminal source coding problems, each subject to distortion constraints computed using a specific, entropy-based, distortion measure. We provide the achievable rate distortion region for two cases…

Information Theory · Computer Science 2011-06-02 Thomas Courtade , Richard Wesel

We develop a novel source coding strategy for sampling and monitoring of a Wiener process. For the encoding process, we employ a four level ``quantization'' scheme, which employs monotone function thresholds as opposed to fixed constant…

Information Theory · Computer Science 2025-04-03 Sahan Liyanaarachchi , Ismail Cosandal , Sennur Ulukus

The problem of secure source coding with multiple terminals is extended by considering a remote source whose noisy measurements are the correlated random variables used for secure source reconstruction. The main additions to the problem…

Information Theory · Computer Science 2022-11-10 Onur Günlü , Rafael F. Schaefer , Holger Boche , H. Vincent Poor

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 optimal stopping problems, in which a sequence of independent random variables is drawn from a known continuous density. The objective of such problems is to find a procedure which maximizes the expected reward; this is often…

Probability · Mathematics 2020-12-07 Hugh Entwistle , Christopher Lustri , Georgy Sofronov

We derive a general formula of the minimum achievable rate for fixed-to-variable length coding with a regular cost function by allowing the error probability up to a constant $\varepsilon$. For a fixed-to-variable length code, we call the…

Information Theory · Computer Science 2017-10-11 Hideki Yagi , Ryo Nomura

The efficiency of a code is estimated by its redundancy $R$, while the complexity of a code is estimated by its average delay $\bar N$. In this work we construct word-based codes, for which $R \lesssim \bar N^{-5/3}$. Therefore, word-based…

Information Theory · Computer Science 2007-12-04 G. L. Khodak

Reasoning models often outperform smaller models but at 3--5$\times$ higher cost and added latency. We present entropy-guided refinement: a lightweight, test-time loop that uses token-level uncertainty to trigger a single, targeted…

Artificial Intelligence · Computer Science 2025-09-03 Andrew G. A. Correa , Ana C. H de Matos

We show how universal codes can be used for solving some of the most important statistical problems for time series. By definition, a universal code (or a universal lossless data compressor) can compress any sequence generated by a…

Information Theory · Computer Science 2008-09-09 Boris Ryabko

New non-asymptotic random coding theorems (with error probability $\epsilon$ and finite block length $n$) based on Gallager parity check ensemble and Shannon random code ensemble with a fixed codeword type are established for discrete input…

Information Theory · Computer Science 2013-03-05 En-hui Yang , Jin Meng

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

The Lempel-Ziv universal coding scheme is asymptotically optimal for the class of all stationary ergodic sources. A problem of robustness of this property under small violations of ergodicity is studied. A notion of deficiency of…

Information Theory · Computer Science 2008-06-30 V. V. V'yugin

This paper explores the possibilities and limitations of error correction by the structural simplicity of error mechanisms. Specifically, we consider channel models, called \emph{samplable additive channels}, in which (a) errors are…

Information Theory · Computer Science 2018-05-15 Kenji Yasunaga

Data partitioning that maximizes/minimizes the Shannon entropy, or more generally the R\'enyi entropy is a crucial subroutine in data compression, columnar storage, and cardinality estimation algorithms. These partition algorithms can be…

Data Structures and Algorithms · Computer Science 2025-11-05 Aryan Esmailpour , Sanjay Krishnan , Stavros Sintos