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Rank-metric codes are subspaces of matrices over finite fields endowed with the rank metric and admit a natural tensorial representation. The tensor rank provides a measure of the minimal size of a decomposition of a code into rank-one…

Information Theory · Computer Science 2026-05-22 Matteo Bonini , Eimear Byrne , Giuseppe Cotardo

A partial matrix is a matrix where only some of the entries are given. We determine the maximum rank of the symmetric completions of a symmetric partial matrix where only the diagonal blocks are given and the minimum rank and the maximum…

Rings and Algebras · Mathematics 2013-09-03 Elena Rubei

We reduce the problem of computing the rank and a nullspace basis of a univariate polynomial matrix to polynomial matrix multiplication. For an input n x n matrix of degree d over a field K we give a rank and nullspace algorithm using about…

Symbolic Computation · Computer Science 2007-05-23 Arne Storjohann , Gilles Villard

For a given matrix subspace, how can we find a basis that consists of low-rank matrices? This is a generalization of the sparse vector problem. It turns out that when the subspace is spanned by rank-1 matrices, the matrices can be obtained…

Numerical Analysis · Computer Science 2016-06-29 Yuji Nakatsukasa , Tasuku Soma , André Uschmajew

Necessary and sufficient conditions are given on matrices $A$, $B$ and $S$, having entries in some field $\mathbb F$ and suitable dimensions, such that the linear span of the terms $A^iSB^j$ over $\mathbb F$ is equal to the whole matrix…

Rings and Algebras · Mathematics 2019-02-13 Giacomo Micheli , Joachim Rosenthal , Paolo Vettori

A vector space S of linear operators between finite-dimensional vector spaces U and V is called locally linearly dependent (in abbreviate form: LLD) when every vector x in U is annihilated by a non-zero operator in S. By a duality argument,…

Rings and Algebras · Mathematics 2015-09-01 Clément de Seguins Pazzis

Matrices of (approximate) low rank are pervasive in data science, appearing in recommender systems, movie preferences, topic models, medical records, and genomics. While there is a vast literature on how to exploit low rank structure in…

Machine Learning · Computer Science 2018-05-31 Madeleine Udell , Alex Townsend

We consider the problem of computing the rank of an m x n matrix A over a field. We present a randomized algorithm to find a set of r = rank(A) linearly independent columns in \~O(|A| + r^\omega) field operations, where |A| denotes the…

Data Structures and Algorithms · Computer Science 2015-03-20 Ho Yee Cheung , Tsz Chiu Kwok , Lap Chi Lau

Let $\mathbf{a} = (a_{i})_{i \geq 1}$ be a sequence in a field $\mathbb{F}$, and $f \colon \mathbb{F} \times \mathbb{F} \to \mathbb{F}$ be a function such that $f(a_{i},a_{i}) \neq 0$ for all $i \geq 1$. For any tournament $T$ over $[n]$,…

Combinatorics · Mathematics 2025-06-05 Niranjan Balachandran , Brahadeesh Sankarnarayanan

We develop tractable convex relaxations for rank-constrained quadratic optimization problems over $n \times m$ matrices, a setting for which tractable relaxations are typically only available when the objective or constraints admit spectral…

Optimization and Control · Mathematics 2026-05-22 Ryan Cory-Wright , Jean Pauphilet

A tropical matrix is a matrix defined over the max-plus semiring. For such matrices, there exist several non-coinciding notions of rank: the row rank, the column rank, the Schein/Barvinok rank, the Kapranov rank, or the tropical rank, among…

Rings and Algebras · Mathematics 2013-05-21 Pierre Guillon , Zur Izhakian , Jean Mairesse , Glenn Merlet

An $L$-matrix is a matrix whose off-diagonal entries belong to a set $L$, and whose diagonal is zero. Let $N(r,L)$ be the maximum size of a square $L$-matrix of rank at most $r$. Many applications of linear algebra in extremal combinatorics…

Commutative Algebra · Mathematics 2016-08-22 Boris Bukh

A vertex k-ranking is a labeling of the vertices of a graph with integers from 1 to k so any path connecting two vertices with the same label will pass through a vertex with a greater label. The rank number of a graph is defined to be the…

Combinatorics · Mathematics 2015-03-20 Sitan Chen

Let $W_{k,n}^{i}(m)$ denote a matrix with rows and columns indexed by the $k$-subsets and $n$-subsets, respectively, of an $m$-element set. The row $S$, column $T$ entry of $W_{k,n}^{i}(m)$ is $1$ if $|S \cap T| = i$, and is $0$ otherwise.…

Combinatorics · Mathematics 2023-05-09 Joshua E. Ducey , Colby J. Sherwood

Let $S_{n}$ denote the space of all $n \times n$ real symmetric matrices. For n=2 or n>2 we characterize maps F from $S_{n}$ to $S_{m}$ which preserve adjacency, i.e. if rank(A-B)=1, then rank(F(A)-F(B))=1.

Rings and Algebras · Mathematics 2007-11-16 Peter Legiša

An n\times n matrix M is called a fooling-set matrix of size n, if its diagonal entries are nonzero, whereas for every k\ne \ell we have M_{k,\ell} M_{\ell,k} = 0. Dietzfelbinger, Hromkovi\v{c}, and Schnitger (1996) showed that n \le (\rk…

Combinatorics · Mathematics 2013-05-14 Mirjam Friesen , Dirk Oliver Theis

Two matrices are said to be principal minor equivalent if they have equal corresponding principal minors of all orders. We give a characterization of principal minor equivalence and a deterministic polynomial time algorithm to check if two…

Computational Complexity · Computer Science 2024-10-04 Abhranil Chatterjee , Sumanta Ghosh , Rohit Gurjar , Roshan Raj

A completion of an m-by-n matrix A with entries in {0,1,*} is obtained by setting all *-entries to constants 0 or 1. A system of semi-linear equations over GF(2) has the form Mx=f(x), where M is a completion of A and f:{0,1}^n --> {0,1}^m…

Computational Complexity · Computer Science 2012-04-18 S. Jukna , G. Schnitger

Let $A$ be an $m \times n$ matrix with rank $r$ and spectral decomposition $A = \sum_{i=1}^r \sigma_i u_i v_i^\top,$ where $\sigma_i$ are its singular values, ordered decreasingly, and $u_i, v_i$ are the corresponding left and right…

Numerical Analysis · Mathematics 2026-03-17 Phuc Tran , Van Vu

Finite dimensional linear spaces (both complex and real) with indefinite scalar product [.,.] are considered. Upper and lower bounds are given for the size of an indecomposable matrix that is normal with respect to this scalar product in…

Functional Analysis · Mathematics 2007-05-23 Olga Holtz