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This paper studies the concentration properties of random codes. Specifically, we show that, for discrete memoryless channels, the error exponent of a randomly generated code with pairwise-independent codewords converges in probability to…

Information Theory · Computer Science 2022-03-16 Lan V. Truong , Giuseppe Cocco , Josep Font-Segura , Albert Guillén i Fàbregas

In this paper, new inner and outer bounds on the achievable compression-equivocation rate region for generalized secure data compression with side information are given that do not match in general. In this setup, two senders, Alice and…

Information Theory · Computer Science 2010-04-07 Somayeh Salimi , Mahmoud Salmasizadeh , Mohammad Reza Aref

In this paper, we revisit the discrete lossy Gray-Wyner problem. In particular, we derive its optimal second-order coding rate region, its error exponent (reliability function) and its moderate deviations constant under mild conditions on…

Information Theory · Computer Science 2017-01-05 Lin Zhou , Vincent Y. F. Tan , Mehul Motani

Let $P = \{p(i)\}$ be a measure of strictly positive probabilities on the set of nonnegative integers. Although the countable number of inputs prevents usage of the Huffman algorithm, there are nontrivial $P$ for which known methods find a…

Information Theory · Computer Science 2016-11-17 Michael B. Baer

In this paper we consider the variable-length lossless source coding for discrete memoryless sources. We proposes a new encryption framework for securely transmitting codewords over a noiseless channel. The proposed source encryption…

Information Theory · Computer Science 2026-05-26 Yasutada Oohama , Bagus Santoso

A private compression design problem is studied, where an encoder observes useful data $Y$, wishes to compress it using variable length code and communicates it through an unsecured channel. Since $Y$ is correlated with private data $X$,…

Information Theory · Computer Science 2023-11-21 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

This monograph presents a unified treatment of single- and multi-user problems in Shannon's information theory where we depart from the requirement that the error probability decays asymptotically in the blocklength. Instead, the error…

Information Theory · Computer Science 2015-04-13 Vincent Y. F. Tan

Data deduplication saves storage space by identifying and removing repeats in the data stream. Compared with traditional compression methods, data deduplication schemes are more time efficient and are thus widely used in large scale storage…

Information Theory · Computer Science 2022-05-30 Hao Lou , Farzad Farnoud

This article studies the achievable guarantees on the error rates of certain learning algorithms, with particular focus on refining logarithmic factors. Many of the results are based on a general technique for obtaining bounds on the error…

Machine Learning · Computer Science 2016-09-13 Steve Hanneke

This paper studies the random-coding exponent of joint source-channel coding for a scheme where source messages are assigned to disjoint subsets (referred to as classes), and codewords are independently generated according to a distribution…

Information Theory · Computer Science 2014-02-19 Adrià Tauste Campo , Gonzalo Vazquez-Vilar , Albert Guillén i Fàbregas , Tobias Koch , Alfonso Martinez

This paper describes universal lossless coding strategies for compressing sources on countably infinite alphabets. Classes of memoryless sources defined by an envelope condition on the marginal distribution provide benchmarks for coding…

Statistics Theory · Mathematics 2015-01-05 Stéphane Boucheron , Aurélien Garivier , Elisabeth Gassiat

We propose two types of universal codes that are suited to two asymptotic regimes when the output alphabet is possibly continuous. The first class has the property that the error probability decays exponentially fast and we identify an…

Information Theory · Computer Science 2024-09-10 Masahito Hayashi

Data compression is a well-studied (and well-solved) problem in the setup of long coding blocks. But important emerging applications need to compress data to memory words of small fixed widths. This new setup is the subject of this paper.…

Information Theory · Computer Science 2017-01-12 Ori Rottenstreich , Yuval Cassuto

A general approach is established for deriving one-shot performance bounds for information-theoretic problems on general alphabets beyond countable alphabets. It is mainly based on the quantization idea and a novel form of "likelihood…

Information Theory · Computer Science 2016-07-12 Shengtian Yang , Thomas Honold , Zhaoyang Zhang

This paper considers the subject of information losses arising from the finite datasets used in the training of neural classifiers. It proves a relationship between such losses as the product of the expected total variation of the estimated…

Machine Learning · Computer Science 2020-01-09 Brandon Foggo , Nanpeng Yu , Jie Shi , Yuanqi Gao

The paper presents exponentially-strong converses for source-coding, channel coding, and hypothesis testing problems. More specifically, it presents alternative proofs for the well-known exponentially-strong converse bounds for almost…

Information Theory · Computer Science 2023-01-18 Mustapha Hamad , Michele Wigger , Mireille Sarkiss

We consider a variant of the channel simulation problem with a single input and multiple outputs, where Alice observes a probability distribution $P$ from a set of prescribed probability distributions $\mathbb{\mathcal{P}}$, and sends a…

Information Theory · Computer Science 2021-09-07 Chak Fung Choi , Cheuk Ting Li

We provide a novel upper-bound on Witsenhausen's rate, the rate required in the zero-error analogue of the Slepian-Wolf problem; our bound is given in terms of a new information-theoretic functional defined on a certain graph. We then use…

Information Theory · Computer Science 2010-01-25 Benjamin G. Kelly , Aaron B. Wagner

Secure data compression in the presence of side information at both a legitimate receiver and an eavesdropper is explored. A noise-free, limited rate link between the source and the receiver, whose output can be perfectly observed by the…

Information Theory · Computer Science 2016-11-17 Deniz Gunduz , Elza Erkip , H. Vincent Poor

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
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