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The still-unsolved problem of determining the set of eigenvalues realized by $n$-by-$n$ doubly stochastic matrices, those matrices with row sums and column sums equal to $1$, has attracted much attention in the last century. This problem is…

Spectral Theory · Mathematics 2020-04-06 Eric Jankowski , Charles R. Johnson , Derek Lim

For a matrix ${\bf A}$ with linearly independent columns, this work studies to use its normalization $\bar{\bf A}$ and ${\bf A}$ itself to approximate its orthonormalization $\bf V$. We theoretically analyze the order of the approximation…

Rings and Algebras · Mathematics 2017-01-04 Gen Li , Yuantao Gu

We study solutions of a quadratic matrix equation arising in Riemannian geometry. Let $S$ be a real symmetric $n\times n$-matrix with zeros on the diagonal and let $\theta$ be a real number. We construct nonzero solutions $(S,\theta)$ of…

Group Theory · Mathematics 2023-09-12 Christopher Deninger , Theo Grundhöfer , Linus Kramer

Statistical properties of non--symmetric real random matrices of size $M$, obtained as truncations of random orthogonal $N\times N$ matrices are investigated. We derive an exact formula for the density of eigenvalues which consists of two…

Statistical Mechanics · Physics 2010-10-21 Boris A. Khoruzhenko , Hans-Juergen Sommers , Karol Zyczkowski

We consider quadratic forms of deterministic matrices $A$ evaluated at the random eigenvectors of a large $N \times N$ GOE or GUE matrix, or equivalently evaluated at the columns of a Haar-orthogonal or Haar-unitary random matrix. We prove…

Probability · Mathematics 2022-10-10 Laszlo Erdos , Benjamin McKenna

We develop a stochastic differential equation, called homogenized SGD, for analyzing the dynamics of stochastic gradient descent (SGD) on a high-dimensional random least squares problem with $\ell^2$-regularization. We show that homogenized…

Statistics Theory · Mathematics 2022-05-17 Courtney Paquette , Elliot Paquette , Ben Adlam , Jeffrey Pennington

The work reported in this article presents a high-order, stable, and efficient Gegenbauer pseudospectral method to solve numerically a wide variety of mathematical models. The proposed numerical scheme exploits the stability and the…

Numerical Analysis · Mathematics 2023-03-06 Kareem T. Elgindy

In this paper, we study the multi-dimensional backward stochastic differential equations (BSDEs) whose generator depends also on the mean of both variables. When the generator is diagonally quadratic, we prove that the BSDE admits a unique…

Probability · Mathematics 2023-03-31 Shanjian Tang , Guang Yang

Given a set of $n$ distinct real numbers, our goal is to form a symmetric, unreduced, tridiagonal, matrix with those numbers as eigenvalues. We give an algorithm which is a stable implementation of a naive algorithm forming the…

Numerical Analysis · Mathematics 2023-11-07 Luca Dieci , Alessandro Pugliese

We consider structural equation models (SEMs), in which every variable is a function of a subset of the other variables and a stochastic error. Each such SEM is naturally associated with a directed graph describing the relationships between…

Combinatorics · Mathematics 2023-08-04 Mathias Drton , Benjamin Hollering , Jun Wu

In this paper, we consider a class of backward doubly stochastic differential equations (BDSDE for short) with general terminal value and general random generator. Those BDSDEs do not involve any forward diffusion processes. By using the…

Probability · Mathematics 2017-02-06 Yaozhong Hu , David Nualart , Xiaoming Song

Data in many applications follows systems of Ordinary Differential Equations (ODEs). This paper presents a novel algorithmic and symbolic construction for covariance functions of Gaussian Processes (GPs) with realizations strictly following…

Machine Learning · Computer Science 2022-08-29 Andreas Besginow , Markus Lange-Hegermann

A generalized eigenvector of a hypermatrix, called the universal (U-) eigenvector, is proposed, which extended the notion of diagonal (D-) eigenvectors in the literature. Using the semi-tensor product, the homogeneous U-eigenequation can be…

Numerical Analysis · Mathematics 2025-07-08 Daizhan Cheng , Zhengping Ji

We introduce the notions of $d$-orthostochastic, $d$-unistochastic, and $d$-qustochastic matrices. These are the particular cases of $F^d$-bistochastic matrices where $F$ is real or complex numbers or quaternions. The concept is motivated…

Mathematical Physics · Physics 2015-06-12 Eugene Gutkin

In this paper, we present four constructions of {general} self-orthogonal matrix-product codes associated with Toeplitz matrices. The first one relies on the {dual} of a known {general} dual-containing matrix-product code; the second one is…

Information Theory · Computer Science 2024-11-26 Yang Li , Shixin Zhu , Edgar Martínez-Moro

We propose a scalable algorithmic framework for exact Bayesian variable selection and model averaging in linear models under the assumption that the Gram matrix is block-diagonal, and as a heuristic for exploring the model space for general…

Computation · Statistics 2017-01-04 Omiros Papaspiliopoulos , David Rossell

In this paper, we study the doubly reflected backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs for short) when the generator has quadratic growth in the $z$-component. Based on the theory of $G$-BMO…

Probability · Mathematics 2026-04-28 Hanwu Li , Peng Luo , Mengbo Zhu

Special orthogonal matrices with rational elements form the group SO(n,Q), where Q is the field of rational numbers. A theorem describing the structure of an arbitrary matrix from this group is proved. This theorem yields an algorithm for…

Mathematical Software · Computer Science 2009-10-14 Ruslan Sharipov

Standard Gibbs sampling applied to a multivariate normal distribution with a specified precision matrix is equivalent in fundamental ways to the Gauss-Seidel iterative solution of linear equations in the precision matrix. Specifically, the…

Computation · Statistics 2015-05-14 Colin Fox , Albert Parker

For every $2n\times 2n$ real positive definite matrix $A,$ there exists a real symplectic matrix $M$ such that $M^TAM=\diag(D,D),$ where $D$ is the $n\times n$ positive diagonal matrix with diagonal entries $d_1(A)\le \cdots\le d_n(A).$ The…

Functional Analysis · Mathematics 2021-08-25 Tanvi Jain
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