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We study perfect error-correcting codes in $\mathbb{Z}^n$ for the symmetric limited-magnitude error channel, where at most $e$ coordinates of an integer vector may be altered by a value whose magnitude is at most $s$. Geometrically, such…

Information Theory · Computer Science 2026-01-21 Zhihao Guan , Hengjia Wei

Optimal modulation (OM) schemes for Gaussian channels with peak and average power constraints are known to require nonuniform probability distributions over signal points, which presents practical challenges. An established way to map…

Information Theory · Computer Science 2022-11-01 Basak Ozaydin , Muriel Médard , Ken Duffy

In this paper we show the usability of the Gray code with constant weight words for computing linear combinations of codewords. This can lead to a big improvement of the computation time for finding the minimum distance of a code. We have…

Information Theory · Computer Science 2018-09-12 Nikolay Yankov , Krassimir Enev

The Cayley distance between two permutations $\pi, \sigma \in S_n$ is the minimum number of \textit{transpositions} required to obtain the permutation $\sigma$ from $\pi$. When we only allow adjacent transpositions, the minimum number of…

Combinatorics · Mathematics 2024-09-09 The Nguyen

Gallager-type error-correcting codes that nearly saturate Shannon's bound are constructed using insight gained from mapping the problem onto that of an Ising spin system. The performance of the suggested codes is evaluated for different…

Disordered Systems and Neural Networks · Physics 2009-10-31 Ido Kanter , David Saad

The past decade has seen a flurry of research into pattern avoiding permutations but little of it is concerned with their exhaustive generation. Many applications call for exhaustive generation of permutations subject to various constraints…

Combinatorics · Mathematics 2008-01-09 W. M. B. Dukes , Mark F. Flanagan , Toufik Mansour , V. Vajnovszki

We investigate the relation between the girth and the guaranteed error correction capability of $\gamma$-left regular LDPC codes when decoded using the bit flipping (serial and parallel) algorithms. A lower bound on the number of variable…

Information Theory · Computer Science 2016-11-17 Shashi Kiran Chilappagari , Dung Viet Nguyen , Bane Vasic , Michael Marcellin

Sign-based algorithms (e.g. signSGD) have been proposed as a biased gradient compression technique to alleviate the communication bottleneck in training large neural networks across multiple workers. We show simple convex counter-examples…

Machine Learning · Computer Science 2019-05-30 Sai Praneeth Karimireddy , Quentin Rebjock , Sebastian U. Stich , Martin Jaggi

We give an improved upper bound for the Gr\"unbaum--Hadwiger--Ramos problem: Let $d,n,k \in \mathbb{N}$ such that $d \geq 2^n(1+2^{k-1})$. Given $2^{n+1}$ masses on $\mathbb{R}^d$, there exist $k$ hyperplanes in $\mathbb{R}^d$ that…

Combinatorics · Mathematics 2022-03-28 Jonathan Kliem

Short-length Reed--Muller codes under majority-logic decoding are of particular importance for efficient hardware implementations in real-time and embedded systems. This paper significantly improves Chen's two-step majority-logic decoding…

Information Theory · Computer Science 2013-10-17 Peter Hauck , Michael Huber , Juliane Bertram , Dennis Brauchle , Sebastian Ziesche

In this paper we study properties and invariants of matrix codes endowed with the rank metric, and relate them to the covering radius. We introduce new tools for the analysis of rank-metric codes, such as puncturing and shortening…

Combinatorics · Mathematics 2016-09-01 Eimear Byrne , Alberto Ravagnani

We introduce a new weight and corresponding metric over finite extension fields for asymmetric error correction. The weight distinguishes between elements from the base field and the ones outside of it, which is motivated by asymmetric…

Information Theory · Computer Science 2024-06-26 Markus Grassl , Anna-Lena Horlemann , Violetta Weger

Maximum-likelihood (ML) decoding can be used to obtain the optimal performance of error correction codes. However, the size of the search space and consequently the decoding complexity grows exponentially, making it impractical to be…

Information Theory · Computer Science 2022-05-25 Mohammad Rowshan , Jinhong Yuan

In this work, we study linear error-correcting codes against adversarial insertion-deletion (indel) errors. While most constructions for the indel model are nonlinear, linear codes offer compact representations, efficient encoding, and…

Information Theory · Computer Science 2025-10-01 Roee Gross , Roni Con , Eitan Yaakobi

This paper introduces a random modulation technique that is decoupled from the channel matrix, allowing it to be applied to arbitrary norm-bounded and spectrally convergent channel matrices. The proposed random modulation constructs an…

Information Theory · Computer Science 2026-01-01 Lei Liu , Yuhao Chi , Shunqi Huang

In this paper we describe a variation of the classical permutation decoding algorithm that can be applied to any affine-invariant code with respect to certain type of information sets. In particular, we can apply it to the family of…

Information Theory · Computer Science 2023-02-13 José Joaquín Bernal , Juan Jacobo Simón

The problem of correcting transpositions (or swaps) of consecutive symbols in $ q $-ary strings is studied. Lower bounds on asymptotically achievable rates of codes correcting $ t = \tau n $ transpositions are derived. The first bound is…

Information Theory · Computer Science 2026-01-06 Mladen Kovačević , Keshav Goyal , Han Mao Kiah

The great success neural networks have achieved is inseparable from the application of gradient-descent (GD) algorithms. Based on GD, many variant algorithms have emerged to improve the GD optimization process. The gradient for…

Machine Learning · Computer Science 2023-05-29 Zefan Li , Bingbing Ni , Teng Li , WenJun Zhang , Wen Gao

The Knill-Laflamme (KL) conditions distinguish exact quantum error correction codes, and it has played a critical role in the discovery of state-of-the-art codes. However, the family of exact codes is a very restrictive one and does not…

Quantum Physics · Physics 2024-06-21 Guo Zheng , Wenhao He , Gideon Lee , Liang Jiang

Low rank approximation is an important tool used in many applications of signal processing and machine learning. Recently, randomized sketching algorithms were proposed to effectively construct low rank approximations and obtain approximate…

Information Theory · Computer Science 2018-09-11 Shashanka Ubaru , Arya Mazumdar , Yousef Saad
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