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A question of Bergman asks whether the adjoint of the generic square matrix over a field can be factored nontrivially as a product of square matrices. We show that such factorizations indeed exist over any coefficient ring when the matrix…

Commutative Algebra · Mathematics 2007-05-23 Ragnar-Olaf Buchweitz , Graham J. Leuschke

Recent work in machine learning community proposed multiple methods for performing lossy compression (quantization) of large matrices. This quantization is important for accelerating matrix multiplication (main component of large language…

Information Theory · Computer Science 2025-10-16 Or Ordentlich , Yury Polyanskiy

We prove that the class of GUM matrices is the largest class of bi-potential matrices stable under Hadamard increasing functions. We also show that any power greater than 1, in the sense of Hadamard functions, of an inverse M-matrix is also…

Probability · Mathematics 2007-05-23 Claude Dellacherie , Servet Martinez , Jaime San Martin

Given a real matrix A with n columns, the problem is to approximate the Gram product AA^T by c << n weighted outer products of columns of A. Necessary and sufficient conditions for the exact computation of AA^T (in exact arithmetic) from c…

Numerical Analysis · Mathematics 2014-05-16 John T. Holodnak , Ilse C. F. Ipsen

In this article, we obtain a super-exponential rate of convergence in total variation between the traces of the first $m$ powers of an $n\times n$ random unitary matrices and a $2m$-dimensional Gaussian random variable. This generalizes…

Probability · Mathematics 2020-02-06 Kurt Johansson , Gaultier Lambert

We consider the problem of finding a dense submatrix of a matrix with i.i.d. Gaussian entries, where density is measured by average value. This problem arose from practical applications in biology and social sciences…

Probability · Mathematics 2025-07-28 Shankar Bhamidi , David Gamarnik , Shuyang Gong

We study the Gaussian and robust covariance estimation, assuming the true covariance matrix to be a Kronecker product of two lower dimensional square matrices. In both settings we define the estimators as solutions to the constrained…

Applications · Statistics 2016-03-28 Ilya Soloveychik , Dmitry Trushin

Let $G, G_1,\dots,G_N$ be independent copies of a standard gaussian random vector in $\mathbb{R}^d$ and denote by $\Gamma = \sum_{i=1}^N \langle G_i,\cdot\rangle e_i$ the standard gaussian ensemble. We show that, for any set $A\subset…

Probability · Mathematics 2026-03-19 Daniel Bartl , Shahar Mendelson

We study the maximum absolute value of the determinant of matrices with entries in the set of $\ell$-th roots of unity; this is a generalization of $D$-optimal designs and Hadamard's maximal determinant problem, which involves $\pm 1$…

Combinatorics · Mathematics 2025-03-17 Guillermo Nuñez Ponasso

The Gaussian expansion has been developed since early 80s as a powerful analytical method, which enables nonperturbative studies of various systems using `perturbative' calculations. Recently the method has been used to suggest that 4d…

High Energy Physics - Theory · Physics 2009-11-10 Jun Nishimura , Toshiyuki Okubo , Fumihiko Sugino

The assumption of Gaussian or Gaussian mixture data has been extensively exploited in a long series of precise performance analyses of machine learning (ML) methods, on large datasets having comparably numerous samples and features. To…

Machine Learning · Statistics 2025-03-14 Xiaoyi Mai , Zhenyu Liao

A natural definition of the product of infinite matrices mimics the usual formulation of multiplication of finite matrices with the caveat (in the absence of any sense of convergence) that the intersection of the support of each row of the…

Rings and Algebras · Mathematics 2018-03-30 Daniel P. Bossaller , Sergio R. López-Permouth

Models with latent factors recently attract a lot of attention. However, most investigations focus on linear regression models and thus cannot capture nonlinearity. To address this issue, we propose a novel Factor Augmented Single-Index…

Methodology · Statistics 2025-01-07 Yanmei Shi , Meiling Hao , Yanlin Tang , Heng Lian , Xu Guo

The cage problem asks for the smallest number $c(k,g)$ of vertices in a $k$-regular graph of girth $g$ and graphs meeting this bound are known as cages. While cages are known to exist for all integers $k \ge 2$ and $g \ge 3$, the exact…

Combinatorics · Mathematics 2018-04-03 John Bamberg , Anurag Bishnoi , Gordon F. Royle

We consider maximum likelihood estimation for Gaussian Mixture Models (Gmms). This task is almost invariably solved (in theory and practice) via the Expectation Maximization (EM) algorithm. EM owes its success to various factors, of which…

Machine Learning · Statistics 2018-06-04 Reshad Hosseini , Suvrit Sra

The problem of matrix factorization motivated by diffraction or elasticity is studied. A powerful tool for analyzing its solutions is introduced, namely analytical continuation formulae are derived. Necessary condition for commutative…

Analysis of PDEs · Mathematics 2012-11-20 Andrey V. Shanin , Eugeny M. Doubravsky

This paper addresses the question of when projections of a high-dimensional random vector are approximately Gaussian. This problem has been studied previously in the context of high-dimensional data analysis, where the focus is on…

Information Theory · Computer Science 2017-01-02 Galen Reeves

Motivated by problems in controlled experiments, we study the discrepancy of random matrices with continuous entries where the number of columns $n$ is much larger than the number of rows $m$. Our first result shows that if $\omega(1) = m =…

Discrete Mathematics · Computer Science 2020-11-10 Paxton Turner , Raghu Meka , Philippe Rigollet

It was conjectured by Gauss that any negative discriminant with at least 32 genera has at least two classes of binary quadratic forms in each genus. We prove that such a discriminant cannot have a particularly large prime factor, by an…

Number Theory · Mathematics 2020-11-19 John Armitage

Consider a $N\times n$ matrix $\Sigma_n=\frac{1}{\sqrt{n}}R_n^{1/2}X_n$, where $R_n$ is a nonnegative definite Hermitian matrix and $X_n$ is a random matrix with i.i.d. real or complex standardized entries. The fluctuations of the linear…

Probability · Mathematics 2016-06-29 Jamal Najim , Jianfeng Yao