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The notion of root polynomials of a polynomial matrix $P(\lambda)$ was thoroughly studied in [F. Dopico and V. Noferini, Root polynomials and their role in the theory of matrix polynomials, Linear Algebra Appl. 584:37--78, 2020]. In this…

Optimization and Control · Mathematics 2022-10-07 Vanni Noferini , Paul Van Dooren

The minimum rank of a simple graph $G$ is defined to be the smallest possible rank over all symmetric real matrices whose $ij$th entry (for $i\neq j$) is nonzero whenever $\{i,j\}$ is an edge in $G$ and is zero otherwise. Minimum rank is a…

Combinatorics · Mathematics 2008-12-05 Laura DeLoss , Jason Grout , Leslie Hogben , Tracy McKay , Jason Smith , Geoff Tims

Matrix sensing has many real-world applications in science and engineering, such as system control, distance embedding, and computer vision. The goal of matrix sensing is to recover a matrix $A_\star \in \mathbb{R}^{n \times n}$, based on a…

Data Structures and Algorithms · Computer Science 2023-03-23 Lianke Qin , Zhao Song , Ruizhe Zhang

We give a new framework for solving the fundamental problem of low-rank matrix completion, i.e., approximating a rank-$r$ matrix $\mathbf{M} \in \mathbb{R}^{m \times n}$ (where $m \ge n$) from random observations. First, we provide an…

Machine Learning · Computer Science 2023-08-08 Jonathan A. Kelner , Jerry Li , Allen Liu , Aaron Sidford , Kevin Tian

The sufficiently scattered condition (SSC) is a key condition in the study of identifiability of various matrix factorization problems, including nonnegative, minimum-volume, symmetric, simplex-structured, and polytopic matrix…

Machine Learning · Computer Science 2025-01-10 Nicolas Gillis , Robert Luce

Exceptional mathematical reasoning ability is one of the key features that demonstrate the power of large language models (LLMs). How to comprehensively define and evaluate the mathematical abilities of LLMs, and even reflect the user…

Computation and Language · Computer Science 2024-10-10 Zihao Zhou , Shudong Liu , Maizhen Ning , Wei Liu , Jindong Wang , Derek F. Wong , Xiaowei Huang , Qiufeng Wang , Kaizhu Huang

We consider the set of $n\times n$ matrices with rational entries having numerator and denominator of size at most $H$ and obtain upper and lower bounds on the number of such matrices of a given rank and then apply them to count such…

Number Theory · Mathematics 2026-03-04 Muhammad Afifurrahman , Vivian Kuperberg , Alina Ostafe , Igor E. Shparlinski

A {\it sign pattern matrix} is a matrix whose entries are from the set $\{+,-, 0\}$. The minimum rank of a sign pattern matrix $A$ is the minimum of the ranks of the real matrices whose entries have signs equal to the corresponding entries…

Combinatorics · Mathematics 2013-12-23 Marina Arav , Frank J. Hall , Zhongshan Li , Hein van der Holst , John Sinkovic , Lihua Zhang

We examine so-called rank function equations and their solutions consisting of non-nilpotent matrices. Secondly, we present some geometrical properties of the set of solutions to certain rank function equations in the nilpotent case.

Rings and Algebras · Mathematics 2023-04-21 Piotr Pokora

How many random entries of an n by m, rank r matrix are necessary to reconstruct the matrix within an accuracy d? We address this question in the case of a random matrix with bounded rank, whereby the observed entries are chosen uniformly…

Data Structures and Algorithms · Computer Science 2008-12-16 Raghunandan H. Keshavan , Andrea Montanari , Sewoong Oh

A novel lower bound is introduced for the full rank probability of random finite field matrices, where a number of elements with known location are identically zero, and remaining elements are chosen independently of each other, uniformly…

Information Theory · Computer Science 2016-08-17 Daniel Salmond , Alex Grant , Ian Grivell , Terence Chan

We propose $\textsf{ScaledGD($\lambda$)}$, a preconditioned gradient descent method to tackle the low-rank matrix sensing problem when the true rank is unknown, and when the matrix is possibly ill-conditioned. Using overparametrized factor…

Machine Learning · Computer Science 2026-01-01 Xingyu Xu , Yandi Shen , Yuejie Chi , Cong Ma

Learning-to-rank (LTR) is a class of supervised learning techniques that apply to ranking problems dealing with a large number of features. The popularity and widespread application of LTR models in prioritizing information in a variety of…

Machine Learning · Computer Science 2020-05-19 Jaspreet Singh , Zhenye Wang , Megha Khosla , Avishek Anand

In this paper, we introduce and study the notion of phase rank. Given a matrix filled with phases, i.e., with complex entries of modulus $1$, its phase rank is the smallest possible rank for a complex matrix with the same phase, but…

Algebraic Geometry · Mathematics 2021-11-04 António Pedro Goucha , João Gouveia

Consider a random vector $(X,Y)$ and let $m(x)=E(Y|X=x)$. We are interested in testing $H_0:m\in {\cal M}_{\Theta,{\cal G}}=\{\gamma(\cdot,\theta,g):\theta \in \Theta,g\in {\cal G}\}$ for some known function $\gamma$, some compact set…

Statistics Theory · Mathematics 2008-07-16 Ingrid Van Keilegom , César Sánchez Sellero , Wenceslao González Manteiga

The task of reconstructing a matrix given a sample of observedentries is known as the matrix completion problem. It arises ina wide range of problems, including recommender systems, collaborativefiltering, dimensionality reduction, image…

Statistics Theory · Mathematics 2014-12-20 Jean Lafond , Olga Klopp , Eric Moulines , Jospeh Salmon

Let $\mathbf{A}_{n,m;k}$ be a random $n \times m$ matrix with entries from some field $\mathbb{F}$ where there are exactly $k$ non-zero entries in each column, whose locations are chosen independently and uniformly at random from the set of…

Combinatorics · Mathematics 2020-02-20 Colin Cooper , Alan Frieze , Wesley Pegden

Economic models may exhibit incompleteness depending on whether or not they admit certain policy-relevant features such as strategic interaction, self-selection, or state dependence. We develop a novel test of model incompleteness and…

Econometrics · Economics 2023-09-08 Shuowen Chen , Hiroaki Kaido

Low rank inference on matrices is widely conducted by optimizing a cost function augmented with a penalty proportional to the nuclear norm $\Vert \cdot \Vert_*$. However, despite the assortment of computational methods for such problems,…

Machine Learning · Statistics 2025-10-08 Simon Segert , Nathan Wycoff

In this paper we derive new sufficient conditions for a linear system matrix $$S(\lambda):=\left[\begin{array}{ccc} T(\lambda) & -U(\lambda) \\ V(\lambda) & W(\lambda) \end{array}\right],$$ where $T(\lambda)$ is assumed regular, to be…

Dynamical Systems · Mathematics 2021-03-10 Froilán M. Dopico , María C. Quintana , Paul Van Dooren
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