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We study universal compression of sequences generated by monotonic distributions. We show that for a monotonic distribution over an alphabet of size $k$, each probability parameter costs essentially $0.5 \log (n/k^3)$ bits, where $n$ is the…

Information Theory · Computer Science 2007-07-13 Gil I. Shamir

Let C be a linear code with length n and minimum distance d. The stopping redundancy of C is defined as the minimum number of rows in a parity-check matrix for C such that the smallest stopping sets in the corresponding Tanner graph have…

Information Theory · Computer Science 2007-07-13 Junsheng Han , Paul H. Siegel

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 study the redundancy of universally compressing strings $X_1,\dots, X_n$ generated by a binary Markov source $p$ without any bound on the memory. To better understand the connection between compression and estimation in the Markov…

Information Theory · Computer Science 2018-06-21 Changlong Wu , Maryam Hosseini , Narayana Santhanam

As techniques for fault-tolerant quantum computation keep improving, it is natural to ask: what is the fundamental lower bound on redundancy? In this paper, we obtain a lower bound on the redundancy required for $\epsilon$-accurate…

Quantum Physics · Physics 2023-08-23 Uthirakalyani G , Anuj K. Nayak , Avhishek Chatterjee

This paper deals with the problem of universal lossless coding on a countable infinite alphabet. It focuses on some classes of sources defined by an envelope condition on the marginal distribution, namely exponentially decreasing envelope…

Information Theory · Computer Science 2011-07-07 Dominique Bontemps

It is now well known that the performance of a linear code $C$ under iterative decoding on a binary erasure channel (and other channels) is determined by the size of the smallest stopping set in the Tanner graph for $C$. Several recent…

Information Theory · Computer Science 2007-07-16 Moshe Schwartz , Alexander Vardy

A left-corner parsing algorithm with top-down filtering has been reported to show very efficient performance for unification-based systems. However, due to the nontermination of parsing with left-recursive grammars, top-down constraints…

cmp-lg · Computer Science 2008-02-03 Noriko Tomuro

Efficient optimal prefix coding has long been accomplished via the Huffman algorithm. However, there is still room for improvement and exploration regarding variants of the Huffman problem. Length-limited Huffman coding, useful for many…

Information Theory · Computer Science 2007-07-13 Michael B. Baer

A new run length encoding algorithm for lossless data compression that exploits positional redundancy by representing data in a two-dimensional model of concentric circles is presented. This visual transform enables detection of runs (each…

Data Structures and Algorithms · Computer Science 2021-07-30 Pranav Venkatram

Finding tight bounds on the optimal solution is a critical element of practical solution methods for discrete optimization problems. In the last decade, decision diagrams (DDs) have brought a new perspective on obtaining upper and lower…

Artificial Intelligence · Computer Science 2019-02-28 Quentin Cappart , Emmanuel Goutierre , David Bergman , Louis-Martin Rousseau

In prefix coding over an infinite alphabet, methods that consider specific distributions generally consider those that decline more quickly than a power law (e.g., Golomb coding). Particular power-law distributions, however, model many…

Information Theory · Computer Science 2009-03-06 Michael B. Baer

The objective of this paper is to improve the customary definition of redundancy by providing quantitative measures in its place, which we coin upper and lower redundancies, that match better with an intuitive understanding of redundancy…

Functional Analysis · Mathematics 2009-11-19 Bernhard G. Bodmann , Peter G. Casazza , Gitta Kutyniok

We study worst-case signal compression under an $\ell^2$ energy constraint, with coordinate-dependent quantization precisions. The compression problem is reduced to counting lattice points in a diagonal ellipsoid. Under balanced precision…

Information Theory · Computer Science 2026-04-06 A. Iosevich , A. Vagharshakyan , E. Wyman

We consider upper bounds on the error probability in channel coding. We derive an improved maximum-likelihood union bound, which takes into account events where the likelihood of the correct codeword is tied with that of some competitors.…

Information Theory · Computer Science 2013-02-12 Eli Haim , Yuval Kochman , Uri Erez

Recently, it has been shown that the max flow capacity can be achieved in a multicast network using network coding. In this paper, we propose and analyze a more realistic model for wireless random networks. We prove that the capacity of…

Information Theory · Computer Science 2008-11-11 Salah A. Aly , Vishal Kapoor , Jie Meng , Andreas Klappenecker

We consider a standard distributed optimisation setting where $N$ machines, each holding a $d$-dimensional function $f_i$, aim to jointly minimise the sum of the functions $\sum_{i = 1}^N f_i (x)$. This problem arises naturally in…

Machine Learning · Computer Science 2021-12-08 Dan Alistarh , Janne H. Korhonen

Function-correcting codes (FCCs) protect specific function evaluations of a message against errors. This condition imposes a less stringent distance requirement than classical error-correcting codes (ECCs), allowing for reduced redundancy.…

Information Theory · Computer Science 2025-07-15 Hoang Ly , Emina Soljanin

This thesis makes several significant contributions to the theory of both Regenerating (RG) and Locally Recoverable (LR) codes. The two principal contributions are characterizing the optimal rate of an LR code designed to recover from $t$…

Information Theory · Computer Science 2018-06-13 S. B. Balaji , P. Vijay Kumar

We derive a new upper bound on the reliability function for channel coding over discrete memoryless channels. Our bounding technique relies on two main elements: (i) adding an auxiliary genie-receiver that reveals to the original receiver a…

Information Theory · Computer Science 2022-09-05 Anelia Somekh-Baruch