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Related papers: On the Sparseness of Certain MRD Codes

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This book is organized into six chapters. The first chapter introduces the basic algebraic structures essential to make this book a self contained one. Algebraic linear codes and their basic properties are discussed in chapter two. In…

General Mathematics · Mathematics 2012-05-04 W. B. Vasantha Kandasamy , Florentin Smarandache , R. Sujatha , R. S. Raja Durai

The paper introduces new bounds on the asymptotic density of parity-check matrices and the achievable rates under ML decoding of binary linear block codes transmitted over memoryless binary-input output-symmetric channels. The lower bounds…

Information Theory · Computer Science 2007-07-13 Gil Wiechman , Igal Sason

This paper investigates general properties of codes with the rank metric. We first investigate asymptotic packing properties of rank metric codes. Then, we study sphere covering properties of rank metric codes, derive bounds on their…

Information Theory · Computer Science 2007-07-13 Maximilien Gadouleau , Zhiyuan Yan

Range minimum queries (RMQs) are fundamental operations with widespread applications in database management, text indexing and computational biology. While many space-efficient data structures have been designed for RMQs on arrays with…

Data Structures and Algorithms · Computer Science 2026-04-16 Seungbum Jo , Srinivasa Rao Satti

We introduce a family of linear sets of $\mathrm{PG}(1,q^{2n})$ arising from maximum scattered linear sets of pseudoregulus type of $\mathrm{PG}(3,q^{n})$. For $n=3,4$ and for certain values of the parameters we show that these linear sets…

Combinatorics · Mathematics 2017-07-27 Bence Csajbók , Giuseppe Marino , Olga Polverino , Corrado Zanella

3D neural networks have become prevalent for many 3D vision tasks including object detection, segmentation, registration, and various perception tasks for 3D inputs. However, due to the sparsity and irregularity of 3D data, custom 3D…

Computer Vision and Pattern Recognition · Computer Science 2022-04-11 Junha Lee , Christopher Choy , Jaesik Park

Sparse linear regression -- finding an unknown vector from linear measurements -- is now known to be possible with fewer samples than variables, via methods like the LASSO. We consider the multiple sparse linear regression problem, where…

Machine Learning · Computer Science 2012-02-28 Ali Jalali , Pradeep Ravikumar , Sujay Sanghavi

This paper is concerned with a covering problem of Euclidean space by a particular arrangement of cones that are not necessarily full and are allowed to overlap. The problem provides an equivalent geometric reformulation of the solvability…

Optimization and Control · Mathematics 2026-02-11 Khalil Ghorbal , Christelle Kozaily

Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points…

Computer Vision and Pattern Recognition · Computer Science 2016-11-03 Jim Jing-Yan Wang , Xuefeng Cui , Ge Yu , Lili Guo , Xin Gao

We prove that a random linear code over F_q, with probability arbitrarily close to 1, is list decodable at radius (1-1/q-\epsilon) with list size L=O(1/\epsilon^2) and rate R=\Omega_q(\epsilon^2/(log^3(1/\epsilon))). Up to the…

Information Theory · Computer Science 2012-07-06 Mahdi Cheraghchi , Venkatesan Guruswami , Ameya Velingker

Sparse coding has been proposed as a theory of visual cortex and as an unsupervised algorithm for learning representations. We show empirically with the MNIST dataset that sparse codes can be very sensitive to image distortions, a behavior…

Computer Vision and Pattern Recognition · Computer Science 2022-04-18 Kyle Luther , H. Sebastian Seung

In this work, we determine new linear equations for the weight distribution of linear codes over finite chain rings. The identities are determined by counting the number of some special submatrices of the parity-check matrix of the code.…

Information Theory · Computer Science 2022-10-31 Giulia Cavicchioni , Alessio Meneghetti

Sparse coding is a crucial subroutine in algorithms for various signal processing, deep learning, and other machine learning applications. The central goal is to learn an overcomplete dictionary that can sparsely represent a given input…

Machine Learning · Statistics 2017-12-14 Thanh V. Nguyen , Raymond K. W. Wong , Chinmay Hegde

An erasure channel with a fixed alphabet size $q$, where $q \gg 1$, is studied. It is proved that over any erasure channel (with or without memory), Maximum Distance Separable (MDS) codes achieve the minimum probability of error (assuming…

Information Theory · Computer Science 2008-06-06 Shervan Fashandi , Shahab Oveis Gharan , Amir K. Khandani

A method for improving the performance of sparse-matrix based parity check codes is proposed, based on insight gained from methods of statistical physics. The advantages of the new approach are demonstrated on an existing encoding/decoding…

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

Reducible codes for the rank metric were introduced for cryptographic purposes. They have fast encoding and decoding algorithms, include maximum rank distance (MRD) codes and can correct many rank errors beyond half of their minimum rank…

Information Theory · Computer Science 2017-08-07 Umberto Martínez-Peñas

In 2013, Bollob\'as, Mitsche, and Pralat at gave upper and lower bounds for the likely metric dimension of random Erd\H{o}s-R\'enyi graphs $G(n,p)$ for a large range of expected degrees $d=pn$. However, their results only apply when $d \ge…

Combinatorics · Mathematics 2025-05-01 Josep Díaz , Harrison Hartle , Cristopher Moore

Let $\cal M$ denote the set ${\cal S}_{n, q}$ of $n \times n$ symmetric matrices with entries in ${\rm GF}(q)$ or the set ${\cal H}_{n, q^2}$ of $n \times n$ Hermitian matrices whose elements are in ${\rm GF}(q^2)$. Then $\cal M$ equipped…

Combinatorics · Mathematics 2020-11-16 Antonio Cossidente , Giuseppe Marino , Francesco Pavese

We formulate a generalization of the Restricted Isometry Property (RIP) referred to as the Restricted Quasiconvexity Isometry Property (RQIP) for alpha stable random projections with $0<\alpha<1$. A lower bound on the number of rows for…

Probability · Mathematics 2025-07-04 Sunder Ram Krishnan

Linear error-correcting codes can be used for constructing secret sharing schemes; however finding in general the access structures of these secret sharing schemes and, in particular, determining efficient access structures is difficult.…

Information Theory · Computer Science 2022-06-07 Angela Aguglia , Michela Ceria , Luca Giuzzi