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We advance the Cohn-Umans framework for developing fast matrix multiplication algorithms. We introduce, analyze, and search for a new subclass of strong uniquely solvable puzzles (SUSP), which we call simplifiable SUSPs. We show that these…

Computational Complexity · Computer Science 2023-07-18 Matthew Anderson , Vu Le

A $0,1$ matrix is said to be regular if all of its rows and columns have the same number of ones. We prove that for infinitely many integers $k$, there exists a square regular $0,1$ matrix with binary rank $k$, such that the Boolean rank of…

Combinatorics · Mathematics 2023-02-06 Ishay Haviv , Michal Parnas

This work introduces a new class of symmetric matrix structures, called harmonic structures, which enable the generation of all possible directed transitions $(x_i, x_{i+1})$ over a set of $n$ symbols, without internal repetitions. Unlike…

Combinatorics · Mathematics 2025-06-23 Nicolás Agustín Martínez

In this work, we provide four methods for constructing new maximum sum-rank distance (MSRD) codes. The first method, a variant of cartesian products, allows faster decoding than known MSRD codes of the same parameters. The other three…

Information Theory · Computer Science 2024-02-06 Umberto Martínez-Peñas

We develop a matrix bordering technique that can be applied to an irreducible spectrally arbitrary sign pattern to construct a higher order spectrally arbitrary sign pattern. This technique generalizes a recently developed triangle…

Rings and Algebras · Mathematics 2017-08-31 Dale Olesky , Pauline van den Driessche , Kevin N. Vander Meulen

It is well-known that the evaluation of the permanent of an arbitrary $(-1,1)$-matrix is a formidable problem. Ryser's formula is one of the fastest known general algorithms for computing permanents. In this paper, Ryser's formula has been…

Combinatorics · Mathematics 2013-11-12 José Andrés Armario

The iterative method of Sinkhorn allows, starting from an arbitrary real matrix with non-negative entries, to find a so-called 'scaled matrix' which is doubly stochastic, i.e. a matrix with all entries in the interval (0, 1) and with all…

Mathematical Physics · Physics 2015-02-09 Alexis De Vos , Stijn De Baerdemacker

The well known algorithm of Volker Strassen for matrix multiplication can only be used for $(m2^k \times m2^k)$ matrices. For arbitrary $(n \times n)$ matrices one has to add zero rows and columns to the given matrices to use Strassen's…

Numerical Analysis · Mathematics 2011-05-25 Ivo Hedtke

Matrices $\Phi\in\R^{n\times p}$ satisfying the Restricted Isometry Property (RIP) are an important ingredient of the compressive sensing methods. While it is known that random matrices satisfy the RIP with high probability even for…

Probability · Mathematics 2018-11-19 David Gamarnik

In this paper, we introduce orbit matrices of directed strongly regular graphs (DSRGs). Further, we propose a method of constructing directed strongly regular graphs with prescribed automorphism group using genetic algorithm. In the…

Combinatorics · Mathematics 2024-12-20 Dean Crnković , Andrea Švob , Tin Zrinski

In this paper, we continue the study of Maximally Recoverable (MR) Grid Codes initiated by Gopalan et al. [SODA 2017]. More precisely, we study codes over an $m \times n$ grid topology with one parity check per row and column of the grid…

Information Theory · Computer Science 2026-02-06 Joshua Brakensiek , Manik Dhar , Sivakanth Gopi

We give lower bounds on the largest singular value of arbitrary matrices, some of which are asymptotically tight for almost all matrices. To study when these bounds are exact, we introduce several combinatorial concepts. In particular, we…

Functional Analysis · Mathematics 2007-05-23 Vladimir Nikiforov

Hadamard matrices of order $n$ are conjectured to exist whenever $n$ is $1$, $2$, or a multiple of $4$; a similar conjecture exists for skew Hadamard matrices. We provide constructions covering orders $\le 1208$ of all known Hadamard and…

Combinatorics · Mathematics 2025-09-03 Matteo Cati , Dmitrii V. Pasechnik

In this note, we give a self-contained and elementary proof of the elementary construction of spectral high-dimensional expanders using elementary matrices due to Kaufman and Oppenheim [Proc. 50th ACM Symp. on Theory of Computing (STOC),…

Discrete Mathematics · Computer Science 2022-06-02 Prahladh Harsha , Ramprasad Saptharishi

A sign pattern is a matrix whose entries belong to the set $\{+,-,0\}$. A sign pattern requires a unique inertia if every real matrix in its qualitative class has the same inertia. Symmetric tree sign patterns requiring a unique inertia has…

Combinatorics · Mathematics 2025-09-01 Partha Rana , Sriparna Bandopadhyay

Considering matrices with missing entries, we study NP-hard matrix completion problems where the resulting completed matrix shall have limited (local) radius. In the pure radius version, this means that the goal is to fill in the entries…

Discrete Mathematics · Computer Science 2020-02-06 Tomohiro Koana , Vincent Froese , Rolf Niedermeier

We consider the problem of constructing linear Maximum Distance Separable (MDS) error-correcting codes with generator matrices that are sparsest and balanced. In this context, sparsest means that every row has the least possible number of…

Information Theory · Computer Science 2016-01-28 Wael Halbawi , Zihan Liu , Babak Hassibi

In 2009, G. Gr\"atzer and E. Knapp proved that every planar semimodular lattice has a rectangular extension. We prove that, under reasonable additional conditions, this extension is unique. This theorem naturally leads to a hierarchy of…

Rings and Algebras · Mathematics 2014-12-16 Gábor Czédli

We show how to construct highly symmetric algorithms for matrix multiplication. In particular, we consider algorithms which decompose the matrix multiplication tensor into a sum of rank-1 tensors, where the decomposition itself consists of…

Computational Complexity · Computer Science 2016-12-13 Joshua A. Grochow , Cristopher Moore

Learning of matrix-valued data has recently surged in a range of scientific and business applications. Trace regression is a widely used method to model effects of matrix predictors and has shown great success in matrix learning. However,…

Machine Learning · Statistics 2021-05-06 Chanwoo Lee , Lexin Li , Hao Helen Zhang , Miaoyan Wang
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