English
Related papers

Related papers: Invariants for sum-rank metric codes

200 papers

The relation between stabilizer codes and binary codes provided by Gottesman and Calderbank et al. is a celebrated result, as it allows the lifting of classical codes to quantum codes. An equivalent way to state this result is that the work…

Information Theory · Computer Science 2024-09-18 Vatsal Pramod Jha , Udaya Parampalli , Abhay Kumar Singh

This paper presents encoding and decoding algorithms for several families of optimal rank metric codes whose codes are in restricted forms of symmetric, alternating and Hermitian matrices. First, we show the evaluation encoding is the right…

Information Theory · Computer Science 2022-02-08 Wrya K. Kadir , Chunlei Li , Ferdinando Zullo

Just as rank-metric or Gabidulin codes may be used to construct rate-diversity tradeoff optimal space-time codes, a recently introduced generalization for the sum-rank metric -- linearized Reed-Solomon codes -- accomplishes the same in the…

Information Theory · Computer Science 2021-03-10 Mohannad Shehadeh , Frank R. Kschischang

Error-correcting pairs were introduced independently by Pellikaan and K\"otter as a general method of decoding linear codes with respect to the Hamming metric using coordinatewise products of vectors, and are used for many well-known…

Information Theory · Computer Science 2015-12-29 Umberto Martínez-Peñas , Ruud Pellikaan

Consider a convex function that is invariant under an group of transformations. If it has a minimizer, does it also have an invariant minimizer? Variants of this problem appear in nonparametric statistics and in a number of adjacent fields.…

Statistics Theory · Mathematics 2024-07-22 Peter Orbanz

We present the theory of linear rank-metric codes from the point of view of their fundamental parameters. These are: the minimum rank distance, the rank distribution, the maximum rank, the covering radius, and the field size. The focus of…

Information Theory · Computer Science 2023-12-12 Anina Gruica , Altan B. Kilic , Alberto Ravagnani

Many successful deep learning architectures are equivariant to certain transformations in order to conserve parameters and improve generalization: most famously, convolution layers are equivariant to shifts of the input. This approach only…

Machine Learning · Computer Science 2021-03-31 Allan Zhou , Tom Knowles , Chelsea Finn

This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the…

Numerical Analysis · Mathematics 2013-10-22 Kenneth Lange , Hua Zhou

Low-rank matrix approximation, which aims to construct a low-rank matrix from an observation, has received much attention recently. An efficient method to solve this problem is to convert the problem of rank minimization into a nuclear norm…

Information Theory · Computer Science 2016-09-21 Seyedroohollah Hosseini

Low-rank matrix completion (LRMC) has demonstrated remarkable success in a wide range of applications. To address the NP-hard nature of the rank minimization problem, the nuclear norm is commonly used as a convex and computationally…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Zhijie Wang , Liangtian He , Qinghua Zhang , Jifei Miao , Liang-Jian Deng , Jun Liu

In this paper we introduce a new class of extremal codes, namely the $i$-BMD codes. We show that for this family several of the invariants are determined by the parameters of the underlying code. We refine and extend the notion of an…

Information Theory · Computer Science 2019-12-09 Eimear Byrne , Giuseppe Cotardo , Alberto Ravagnani

We study several variants of decomposing a symmetric matrix into a sum of a low-rank positive semidefinite matrix and a diagonal matrix. Such decompositions have applications in factor analysis and they have been studied for many decades.…

Optimization and Control · Mathematics 2023-10-02 Levent Tunçel , Stephen A. Vavasis , Jingye Xu

We introduce the concept of a sum-rank saturating system and outline its correspondence to a covering properties of a sum-rank metric code. We consider the problem of determining the shortest sum-rank-$\rho$-saturating systems of a fixed…

Combinatorics · Mathematics 2025-04-10 Matteo Bonini , Martino Borello , Eimear Byrne

Symmetric nonnegative matrix factorization (SNMF) is equivalent to computing a symmetric nonnegative low rank approximation of a data similarity matrix. It inherits the good data interpretability of the well-known nonnegative matrix…

Numerical Analysis · Computer Science 2017-10-11 Qingjiang Shi , Haoran Sun , Songtao Lu , Mingyi Hong , Meisam Razaviyayn

Regularization techniques are widely employed in optimization-based approaches for solving ill-posed inverse problems in data analysis and scientific computing. These methods are based on augmenting the objective with a penalty function,…

Optimization and Control · Mathematics 2021-06-08 Yong Sheng Soh , Venkat Chandrasekaran

This paper presents a program analysis method that generates program summaries involving polynomial arithmetic. Our approach builds on prior techniques that use solvable polynomial maps for summarizing loops. These techniques are able to…

Programming Languages · Computer Science 2023-12-08 John Cyphert , Zachary Kincaid

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

In this work, cyclic-skew-cyclic codes and sum-rank BCH codes are introduced. Cyclic-skew-cyclic codes are characterized as left ideals of a suitable non-commutative finite ring, constructed using skew polynomials on top of polynomials (or…

Information Theory · Computer Science 2021-06-09 Umberto Martínez-Peñas

The need to test whether two random vectors are independent has spawned a large number of competing measures of dependence. We are interested in nonparametric measures that are invariant under strictly increasing transformations, such as…

Statistics Theory · Mathematics 2017-08-21 Luca Weihs , Mathias Drton , Nicolai Meinshausen

We derive simplified sphere-packing and Gilbert--Varshamov bounds for codes in the sum-rank metric, which can be computed more efficiently than previous ones. They give rise to asymptotic bounds that cover the asymptotic setting that has…

Information Theory · Computer Science 2023-03-22 Cornelia Ott , Sven Puchinger , Martin Bossert
‹ Prev 1 4 5 6 7 8 10 Next ›