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An enumeration kernel as defined by Creignou et al. [Theory Comput. Syst. 2017] for a parameterized enumeration problem consists of an algorithm that transforms each instance into one whose size is bounded by the parameter plus a…

Data Structures and Algorithms · Computer Science 2021-01-12 Petr A. Golovach , Christian Komusiewicz , Dieter Kratsch , Van Bang Le

The most fundamental model of a molecule is a cloud of unordered atoms, even without chemical bonds that can depend on thresholds for distances and angles. The strongest equivalence between clouds of atoms is rigid motion, which is a…

Computational Geometry · Computer Science 2023-11-01 Vitaliy Kurlin

Given a limited number of entries from the superposition of a low-rank matrix plus the product of a known fat compression matrix times a sparse matrix, recovery of the low-rank and sparse components is a fundamental task subsuming…

Multiagent Systems · Computer Science 2013-10-01 Morteza Mardani , Gonzalo Mateos , Georgios B. Giannakis

We propose a new class of space-time block codes based on finite-field rank-metric codes in combination with a rank-metric-preserving mapping to the set of Eisenstein integers. It is shown that these codes achieve maximum diversity order…

Information Theory · Computer Science 2017-05-30 Sven Puchinger , Sebastian Stern , Martin Bossert , Robert F. H. Fischer

Quantum error correction and symmetries play central roles in quantum information science and physics. It is known that quantum error-correcting codes that obey (are covariant with respect to) continuous symmetries in a certain sense cannot…

Quantum Physics · Physics 2022-04-27 Linghang Kong , Zi-Wen Liu

The sum-rank metric is the mixture of the Hamming and rank metrics. The sum-rank metric found its application in network coding, locally repairable codes, space-time coding, and quantum-resistant cryptography. Linearized Reed-Solomon (LRS)…

Information Theory · Computer Science 2026-02-10 Kuo Shang , Chen Yuan , Ruiqi Zhu

A method is described to probe high-scale physics in lower-energy experiments by employing sum rules in terms of renormalisation group invariants. The method is worked out in detail for the study of supersymmetry-breaking mechanisms in the…

High Energy Physics - Phenomenology · Physics 2012-11-06 Jamil Hetzel , Wim Beenakker

In rank-metric cryptography, a vector from a finite dimensional linear space over a finite field is viewed as the linear space spanned by its entries. The rank decoding problem which is the analogue of the problem of decoding a random…

Cryptography and Security · Computer Science 2023-10-16 Étienne Burle , Philippe Gaborit , Younes Hatri , Ayoub Otmani

For each rank metric code $\mathcal{C}\subseteq \mathbb{K}^{m\times n}$, we associate a translation structure, the kernel of which is shown to be invariant with respect to the equivalence on rank metric codes. When $\mathcal{C}$ is…

Combinatorics · Mathematics 2017-04-20 Guglielmo Lunardon , Rocco Trombetti , Yue Zhou

Association schemes are central objects in algebraic combinatorics, with the classical schemes lying at their core. These classical association schemes essentially consist of the Hamming and Johnson schemes, and their $q$-analogs: bilinear…

Combinatorics · Mathematics 2026-03-30 Kai-Uwe Schmidt , Charlene Weiß

Comparing probability distributions is a core challenge across the natural, social, and computational sciences. Existing methods, such as Maximum Mean Discrepancy (MMD), struggle in high-dimensional and non-compact domains. Here we…

Machine Learning · Statistics 2025-09-09 Logan S. McCarty

Similarity matrix serves as a fundamental tool at the core of numerous downstream machine-learning tasks. However, missing data is inevitable and often results in an inaccurate similarity matrix. To address this issue, Similarity Matrix…

Machine Learning · Computer Science 2024-10-01 Changyi Ma , Runsheng Yu , Xiao Chen , Youzhi Zhang

The sum-rank metric is a hybrid between the Hamming metric and the rank metric and suitable for error correction in multishot network coding and distributed storage as well as for the design of quantum-resistant cryptosystems. In this work,…

Information Theory · Computer Science 2023-03-28 Felicitas Hörmann , Hannes Bartz

We compare the two duality theories of rank-metric codes proposed by Delsarte and Gabidulin, proving that the former generalizes the latter. We also give an elementary proof of MacWilliams identities for the general case of Delsarte…

Information Theory · Computer Science 2015-04-03 Alberto Ravagnani

Symmetric functions, which take as input an unordered, fixed-size set, are known to be universally representable by neural networks that enforce permutation invariance. These architectures only give guarantees for fixed input sizes, yet in…

Machine Learning · Computer Science 2022-10-11 Aaron Zweig , Joan Bruna

The paper addresses parametric inequality systems described by polynomial functions in finite dimensions, where state-dependent infinite parameter sets are given by finitely many polynomial inequalities and equalities. Such systems can be…

Optimization and Control · Mathematics 2015-09-15 G. Li , B. S. Mordukhovich , T. T. A. Nghia , T. S. Pham

A large class of MDS linear codes is constructed. These codes are endowed with an efficient decoding algorithm. Both the definition of the codes and the design of their decoding algorithm only require from Linear Algebra methods, making…

Information Theory · Computer Science 2020-06-02 José Gómez-Torrecillas , Gabriel Navarro , José Patricio Sánchez-Hernández

One central theme in quantum error-correction is to construct quantum codes that have a large minimum distance. In this paper, we first present a construction of classical codes based on certain class of polynomials. Through these classical…

Information Theory · Computer Science 2015-08-06 Tao Zhang , Gennian Ge

The problem of securing a network coding communication system against an eavesdropper adversary is considered. The network implements linear network coding to deliver n packets from source to each receiver, and the adversary can eavesdrop…

Information Theory · Computer Science 2019-05-07 Danilo Silva , Frank R. Kschischang

This paper presents a new similarity measure to be used for general tasks including supervised learning, which is represented by the K-nearest neighbor classifier (KNN). The proposed similarity measure is invariant to large differences in…

Machine Learning · Computer Science 2014-09-04 Ahmad Basheer Hassanat