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We have recently presented a method to solve an overdetermined linear system of equations with multiple right hand side vectors, where the unknown matrix is to be symmetric and positive definite. The coefficient and the right hand side…

Optimization and Control · Mathematics 2014-09-19 Negin Bagherpour , Nezam Mahdavi-Amiri

Matrix pencils, or pairs of matrices, may be used in a variety of applications. In particular, a pair of matrices (E,A) may be interpreted as the differential equation E x' + A x = 0. Such an equation is invariant by changes of variables,…

Numerical Analysis · Mathematics 2012-05-08 Olivier Verdier

We consider ensembles of Wigner matrices, whose entries are (up to the symmetry constraints) independent and identically distributed random variables. We show the convergence of the Stieltjes transform towards the Stieltjes transform of the…

Mathematical Physics · Physics 2014-12-05 Claudio Cacciapuoti , Anna Maltsev , Benjamin Schlein

We pose the problem of the optimal approximation of a given nonnegative signal $y_t$ with the scalar autoconvolution $(x*x)_t$ of a nonnegative signal $x_t$, where $x_t$ and $y_t$ are signals of equal length. The $\mathcal{I}$-divergence…

Optimization and Control · Mathematics 2024-06-04 Lorenzo Finesso , Peter Spreij

Given a square complex matrix $A$, we tackle the problem of finding the nearest matrix with multiple eigenvalues or, equivalently when $A$ had distinct eigenvalues, the nearest defective matrix. To this goal, we extend the general framework…

Numerical Analysis · Mathematics 2026-05-14 Vanni Noferini , Lauri Nyman , Federico Poloni

We study the least squares regression problem \begin{align*} \min_{\Theta \in \mathcal{S}_{\odot D,R}} \|A\Theta-b\|_2, \end{align*} where $\mathcal{S}_{\odot D,R}$ is the set of $\Theta$ for which $\Theta = \sum_{r=1}^{R} \theta_1^{(r)}…

Machine Learning · Computer Science 2017-09-22 Jarvis Haupt , Xingguo Li , David P. Woodruff

Consider two types of products of independent random matrices, including products of Ginibre matrices and inverse Ginibre matrices and products of truncated Haar unitary matrices and inverse truncated Haar matrices. Each product matrix has…

Probability · Mathematics 2025-06-13 Shuhua Chang , Tiefeng Jiang , Yongcheng Qi

The paper is concerned with a sequence of constants which appear in several problems. These problems include the minimal eigenvalue of certain positive definite Toeplitz matrices, the minimal eigenvalue of some higher-order ordinary…

Functional Analysis · Mathematics 2007-05-23 A. Boettcher , H. Widom

The state-of-the-art methods for estimating high-dimensional covariance matrices all shrink the eigenvalues of the sample covariance matrix towards a data-insensitive shrinkage target. The underlying shrinkage transformation is either…

Machine Learning · Statistics 2025-11-25 Man-Chung Yue , Yves Rychener , Daniel Kuhn , Viet Anh Nguyen

Suppose $\{ X_k \}_{k \in \mathbb{Z}}$ is a sequence of bounded independent random matrices with common dimension $d\times d$ and common expectation $\mathbb{E}[ X_k ]= X$. Under these general assumptions, the normalized random matrix…

Probability · Mathematics 2019-07-15 Amelia Henriksen , Rachel Ward

In this note, we consider a sample covariance matrix of the form $$M_{n}=\sum_{\alpha=1}^m \tau_\alpha {\mathbf{y}}_{\alpha}^{(1)} \otimes {\mathbf{y}}_{\alpha}^{(2)}({\mathbf{y}}_{\alpha}^{(1)} \otimes {\mathbf{y}}_{\alpha}^{(2)})^T,$$…

Probability · Mathematics 2024-09-11 Alicja Dembczak-Kołodziejczyk

The joint approximate diagonalization of non-commuting symmetric matrices is an important process in independent component analysis. This problem can be formulated as an optimization problem on the Stiefel manifold that can be solved using…

Optimization and Control · Mathematics 2022-02-28 Hiroyuki Sato

We consider a sparse i.i.d.\ non-Hermitian random matrix model $X_n$ (with sparsity parameter $K_n$) and a deterministic finite-rank perturbation $E_n$. Assuming biorthogonality for $E_n$ and a growth condition on $K_n$, we outline a…

Probability · Mathematics 2026-03-05 Miltiadis Galanis , Michail Louvaris

We obtain a new multiplicative decomposition of the resolvent matrix of the truncated Hausdorff matrix moment (THMM) problem in the case of an odd and even number of moments via new Dyukarev-Stieltjes matrix (DSM) parameters. Explicit…

Classical Analysis and ODEs · Mathematics 2016-10-19 Abdon E. Choque-Rivero

Let $O$ be chosen uniformly at random from the group of $(N+L) \times (N+L)$ orthogonal matrices. Denote by $\tilde{O}$ the upper-left $N \times N$ corner of $O$, which we refer to as a truncation of $O$. In this paper we prove two…

Probability · Mathematics 2025-04-18 Alex Little , Francesco Mezzadri , Nick Simm

This paper considers the problem of solving a special quartic-quadratic optimization problem with a single sphere constraint, namely, finding a global and local minimizer of…

Optimization and Control · Mathematics 2019-08-05 Haixiang Zhang , Andre Milzarek , Zaiwen Wen , Wotao Yin

The study of eigenvalue distributions in random matrix theory is often conducted by analyzing the resolvent matrix $ \mathbf{G}_{\mathbf{M}}^N(z) = (z \mathbf{1} - \mathbf{M})^{-1} $. The normalized trace of the resolvent, known as the…

Mathematical Physics · Physics 2024-12-02 Pierre Bousseyroux , Jean-Philippe Bouchaud , Marc Potters

We analyze the resolvent $R(k)=(P+k^2)^{-1}$ of Schr\"odinger operators $P=\Delta+V$ with short range potential $V$ on asymptotically conic manifolds $(M,g)$ (this setting includes asymptotically Euclidean manifolds) near $k=0$. We make the…

Analysis of PDEs · Mathematics 2007-05-23 Colin Guillarmou , Andrew Hassell

We study the statistics of the local resolvent and non-ergodic properties of eigenvectors for a generalised Rosenzweig-Porter $N\times N$ random matrix model, undergoing two transitions separated by a delocalised non-ergodic phase.…

Disordered Systems and Neural Networks · Physics 2016-09-29 Davide Facoetti , Pierpaolo Vivo , Giulio Biroli

We revisit the classic Wigner semi-circle from two different angles. One consists in studying the Stieltjes transform directly on the real axis, which does not converge to a fixed value but follows a Cauchy distribution that depends on the…

Mathematical Physics · Physics 2018-12-26 J. P. Bouchaud , M. Potters
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