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We consider two matrix completion problems, in which we are given a matrix with missing entries and the task is to complete the matrix in a way that (1) minimizes the rank, or (2) minimizes the number of distinct rows. We study the…

Data Structures and Algorithms · Computer Science 2018-09-14 Robert Ganian , Iyad Kanj , Sebastian Ordyniak , Stefan Szeider

Let $R=K[[x_1,...,x_s]]$ be the ring of formal power series with maximal ideal $\mathfrak{m}$ over a field $K$ of arbitrary characteristic. On the ring $M_{m,n}$ of $m\times n$ matrices $A$ with entries in $R$ we consider several…

Algebraic Geometry · Mathematics 2016-09-19 Gert-Martin Greuel , Thuy Huong Pham

Given a square, nonsingular matrix of univariate polynomials $\mathbf{F}\in\mathbb{K}[x]^{n\times n}$ over a field $\mathbb{K}$, we give a deterministic algorithm for finding the determinant of $\mathbf{F}$. The complexity of the algorithm…

Symbolic Computation · Computer Science 2014-09-22 Wei Zhou , George Labahn

We study the problem of constructing explicit families of matrices which cannot be expressed as a product of a few sparse matrices. In addition to being a natural mathematical question on its own, this problem appears in various…

Computational Complexity · Computer Science 2019-04-03 Mrinal Kumar , Ben Lee Volk

A series-parallel matrix is a binary matrix that can be obtained from an empty matrix by successively adjoining rows or columns that are parallel to an existing row/column or have at most one 1-entry. Equivalently, series-parallel matrices…

Discrete Mathematics · Computer Science 2023-06-27 Matthias Walter

Rank regularized minimization problem is an ideal model for the low-rank matrix completion/recovery problem. The matrix factorization approach can transform the high-dimensional rank regularized problem to a low-dimensional factorized…

Optimization and Control · Mathematics 2024-05-21 Wenjing Li , Wei Bian , Kim-Chuan Toh

To efficiently express tensor data using the Tucker format, a critical task is to minimize the multilinear rank such that the model would not be over-flexible and lead to overfitting. Due to the lack of rank minimization tools in tensor,…

Signal Processing · Electrical Eng. & Systems 2024-09-11 Xueke Tong , Hancheng Zhu , Lei Cheng , Yik-Chung Wu

Let $M_n$ be a random $n\times n$ matrix with i.i.d. $\text{Bernoulli}(1/2)$ entries. We show that for fixed $k\ge 1$, \[\lim_{n\to \infty}\frac{1}{n}\log_2\mathbb{P}[\text{corank }M_n\ge k] = -k.\]

Probability · Mathematics 2021-03-04 Vishesh Jain , Ashwin Sah , Mehtaab Sawhney

Under the action of the general linear group with tensor structure, the ranks of matrices $A$ and $B$ forming an $m \times n$ pencil $A + \lambda B$ can change, but in a restricted manner. Specifically, with every pencil one can associate a…

Numerical Analysis · Mathematics 2018-06-20 José Henrique de Morais Goulart , Pierre Comon

This paper introduces combinatorial representations, which generalise the notion of linear representations of matroids. We show that any family of subsets of the same cardinality has a combinatorial representation via matrices. We then…

Combinatorics · Mathematics 2011-09-07 Peter J. Cameron , Maximilien Gadouleau , Søren Riis

We investigate the complexity of several fundamental polynomial-time solvable problems on graphs and on matrices, when the given instance has low treewidth; in the case of matrices, we consider the treewidth of the graph formed by non-zero…

Data Structures and Algorithms · Computer Science 2015-11-05 Fedor V. Fomin , Daniel Lokshtanov , Michał Pilipczuk , Saket Saurabh , Marcin Wrochna

Given n subspaces of a finite-dimensional vector space over a fixed finite field $\mathbb F$, we wish to find a linear layout $V_1,V_2,\ldots,V_n$ of the subspaces such that $\dim((V_1+V_2+\cdots+V_i) \cap (V_{i+1}+\cdots+V_n))\le k$ for…

Data Structures and Algorithms · Computer Science 2018-05-16 Jisu Jeong , Eun Jung Kim , Sang-il Oum

Motivated by the popularity of stochastic rounding in the context of machine learning and the training of large-scale deep neural network models, we consider stochastic nearness rounding of real matrices $\mathbf{A}$ with many more rows…

Machine Learning · Computer Science 2024-12-10 Gregory Dexter , Christos Boutsikas , Linkai Ma , Ilse C. F. Ipsen , Petros Drineas

Let $\A_0, \A_1, \ldots, \A_n$ be given square matrices of size $m$ with rational coefficients. The paper focuses on the exact computation of one point in each connected component of the real determinantal variety $\{\X \in\RR^n \: :\:…

Symbolic Computation · Computer Science 2014-12-19 Didier Henrion , Simone Naldi , Mohab Safey El Din

The exact nonnegative matrix factorization (exact NMF) problem is the following: given an $m$-by-$n$ nonnegative matrix $X$ and a factorization rank $r$, find, if possible, an $m$-by-$r$ nonnegative matrix $W$ and an $r$-by-$n$ nonnegative…

Optimization and Control · Mathematics 2016-10-07 Arnaud Vandaele , Nicolas Gillis , François Glineur , Daniel Tuyttens

Motivated by recent works on statistics of matrices over sets of number theoretic interest, we study matrices with entries from arbitrary finite subsets $\mathcal A$ of finite rank multiplicative groups infields of characteristic zero. We…

Number Theory · Mathematics 2025-02-12 Aaron Manning , Alina Ostafe , Igor E. Shparlinski

We introduce a "learning-based" algorithm for the low-rank decomposition problem: given an $n \times d$ matrix $A$, and a parameter $k$, compute a rank-$k$ matrix $A'$ that minimizes the approximation loss $\|A-A'\|_F$. The algorithm uses a…

Machine Learning · Computer Science 2019-10-31 Piotr Indyk , Ali Vakilian , Yang Yuan

Gaussian elimination with full pivoting generates a PLUQ matrix decomposition. Depending on the strategy used in the search for pivots, the permutation matrices can reveal some information about the row or the column rank profiles of the…

Numerical Analysis · Computer Science 2013-05-21 Jean-Guillaume Dumas , Clément Pernet , Ziad Sultan

Let $H\_0, ..., H\_n$ be $m \times m$ matrices with entries in $\QQ$ and Hankel structure, i.e. constant skew diagonals. We consider the linear Hankel matrix $H(\vecx)=H\_0+\X\_1H\_1+...+\X\_nH\_n$ and the problem of computing sample points…

Symbolic Computation · Computer Science 2015-02-10 Didier Henrion , Simone Naldi , Mohab Safey El Din

We study the problem of efficiently correcting an erroneous product of two $n\times n$ matrices over a ring. Among other things, we provide a randomized algorithm for correcting a matrix product with at most $k$ erroneous entries running in…

Data Structures and Algorithms · Computer Science 2016-08-19 Leszek Gasieniec , Christos Levcopoulos , Andrzej Lingas , Rasmus Pagh , Takeshi Tokuyama