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The information bottleneck channel (or the oblivious relay channel) concerns a channel coding setting where the decoder does not directly observe the channel output. Rather, the channel output is relayed to the decoder by an oblivious relay…

Information Theory · Computer Science 2026-04-28 Yanxiao Liu , Sepehr Heidari Advary , Cheuk Ting Li

The trade-off capacity region of a quantum channel characterizes the optimal net rates at which a sender can communicate classical, quantum, and entangled bits to a receiver by exploiting many independent uses of the channel, along with the…

Quantum Physics · Physics 2015-03-19 Mark M. Wilde , Patrick Hayden , Saikat Guha

We consider transmission over a binary-input additive white Gaussian noise channel using low-density parity-check codes. One of the most popular techniques for decoding low-density parity-check codes is the linear programming decoder. In…

Information Theory · Computer Science 2015-03-19 Shrinivas Kudekar , Jason K. Johnson , Misha Chertkov

In relative entropy coding, a sender aims to design a stochastic code such that, on input $X \sim P_X$, the receiver can generate a sample $Y \sim P_{Y \mid X}$. It is a standard result that (1) this requires at least $I(X; Y)$ bits, (2)…

Information Theory · Computer Science 2026-05-05 Spencer Hill , Fady Alajaji , Tamás Linder , Gergely Flamich

DNA storage has emerged as a promising solution for large-scale and long-term data preservation. Among various error types, insertions are the most frequent errors occurring in DNA sequences, where the inserted symbol is often identical or…

Information Theory · Computer Science 2026-04-07 Hengfeng Liu , Chunming Tang , Cuiling Fan

A method is proposed, called channel polarization, to construct code sequences that achieve the symmetric capacity $I(W)$ of any given binary-input discrete memoryless channel (B-DMC) $W$. The symmetric capacity is the highest rate…

Information Theory · Computer Science 2016-11-18 Erdal Arikan

An upper limit is given to the amount of quantum information that can be transmitted reliably down a noisy, decoherent quantum channel. A class of quantum error-correcting codes is presented that allow the information transmitted to attain…

Quantum Physics · Physics 2009-10-30 Seth Lloyd

In this paper will be presented new approach to entropy coding: family of generalizations of standard numeral systems which are optimal for encoding sequence of equiprobable symbols, into asymmetric numeral systems - optimal for freely…

Information Theory · Computer Science 2009-05-21 Jarek Duda

Berlekamp and Zigangirov completely determined the capacity error function for binary error correcting codes with noiseless feedback. It is still an unsolved problem if the upper bound for the capacity error function in the non-binary case…

Information Theory · Computer Science 2020-11-20 Christian Deppe , Vladimir Lebedev

The Parity Source Coder is a protocol for data compression which is based on a set of parity checks organized in a sparse random network. We consider here the case of memoryless unbiased binary sources. We show that the theoretical capacity…

Disordered Systems and Neural Networks · Physics 2009-11-11 Stefano Ciliberti , Marc Mezard

We derive an upper bound on the capacity of non-binary deletion channels. Although binary deletion channels have received significant attention over the years, and many upper and lower bounds on their capacity have been derived, such…

Information Theory · Computer Science 2013-10-10 Mojtaba Rahmati , Tolga M. Duman

Improved bounds on the blocklength required to communicate over binary-input channels using polar codes, below some given error probability, are derived. For that purpose, an improved bound on the number of non-polarizing channels is…

Information Theory · Computer Science 2013-07-23 Dina Goldin , David Burshtein

After being trained, classifiers must often operate on data that has been corrupted by noise. In this paper, we consider the impact of such noise on the features of binary classifiers. Inspired by tools for classifier robustness, we…

Machine Learning · Statistics 2017-03-09 Frederic Sala , Shahroze Kabir , Guy Van den Broeck , Lara Dolecek

We introduce a new family of concatenated codes with an outer low-density parity-check (LDPC) code and an inner low-density generator matrix (LDGM) code, and prove that these codes can achieve capacity under any memoryless binary-input…

Information Theory · Computer Science 2016-08-31 Chun-Hao Hsu , Achilleas Anastasopoulos

We consider the compound capacity of polar codes under successive cancellation decoding for a collection of binary-input memoryless output-symmetric channels. By deriving a sequence of upper and lower bounds, we show that in general the…

Information Theory · Computer Science 2009-07-21 S. Hamed Hassani , Satish Babu Korada , Ruediger Urbanke

Recently, a secrecy measure based on list-reconstruction has been proposed [2], in which a wiretapper is allowed to produce a list of $2^{mR_{L}}$ reconstruction sequences and the secrecy is measured by the minimum distortion over the…

Information Theory · Computer Science 2017-07-25 Lei Yu , Houqiang Li , Weiping Li

The performance of iterative decoding techniques for linear block codes correcting erasures depends very much on the sizes of the stopping sets associated with the underlying Tanner graph, or, equivalently, the parity-check matrix…

Information Theory · Computer Science 2007-07-13 Jos H. Weber , Khaled A. S. Abdel-Ghaffar

This paper studies the cardinality of codes correcting insertions and deletions. We give improved upper and lower bounds on code size. Our upper bound is obtained by utilizing the asymmetric property of list decoding for insertions and…

Information Theory · Computer Science 2023-12-14 Kenji Yasunaga

Many probabilistic inference tasks involve summations over exponentially large sets. Recently, it has been shown that these problems can be reduced to solving a polynomial number of MAP inference queries for a model augmented with randomly…

Artificial Intelligence · Computer Science 2013-09-27 Stefano Ermon , Carla P. Gomes , Ashish Sabharwal , Bart Selman

We consider a bound on the bias reduction of a random number generator by processing based on binary linear codes. We introduce a new bound on the total variation distance of the processed output based on the weight distribution of the code…

Information Theory · Computer Science 2014-05-13 Alessio Meneghetti , Massimiliano Sala , Alessandro Tomasi
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