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Learning distributed representations, or embeddings, that encode the relational similarity patterns among objects is a relevant task in machine learning. A popular method to learn the embedding matrices $X, Y$ is optimizing a loss function…

Machine Learning · Computer Science 2025-06-03 Lorenzo Dall'Amico , Enrico Maria Belliardo

We systematically study the first three terms in the asymptotic expansions of the moments of the transmission eigenvalues and proper delay times as the number of quantum channels n in the leads goes to infinity. The computations are based…

Mathematical Physics · Physics 2012-07-02 F. Mezzadri , N. J. Simm

In $M$-estimation under standard asymptotics, the weak convergence combined with the polynomial type large deviation estimate of the associated statistical random field Yoshida (2011) provides us with not only the asymptotic distribution of…

Statistics Theory · Mathematics 2017-04-18 Hiroki Masuda , Yusuke Shimizu

We establish an equidistribution theorem for the common zeros of random sections of high powers of several singular Hermitian big line bundles associated to moderate measures.

Complex Variables · Mathematics 2016-05-18 Guokuan Shao

We revisit the problem of estimates of moments of random n-dimensional matrices of Wigner ensemble by using the approach elaborated by Ya. Sinai and A. Soshnikov and further developed by A. Ruzmaikina. Our main subject is given by the…

Mathematical Physics · Physics 2008-12-29 O. Khorunzhiy , V. Vengerovsky

We determine the distribution of the sandpile group (a.k.a. Jacobian) of the Erd\H{o}s-R\'enyi random graph G(n,q) as n goes to infinity. Since any particular group appears with asymptotic probability 0 (as we show), it is natural ask for…

Probability · Mathematics 2014-06-03 Melanie Matchett Wood

We investigate one-matrix correlation functions for finite SU(N) Yang-Mills integrals with and without supersymmetry. We propose novel convergence conditions for these correlators which we determine from the one-loop perturbative effective…

High Energy Physics - Theory · Physics 2009-10-31 Werner Krauth , Matthias Staudacher

Let ${\cal X }=XX^{\prime}$ be a random matrix associated with a centered $r$-column centered Gaussian vector $X$ with a covariance matrix $P$. In this article we compute expectations of matrix-products of the form $\prod_{1\leq i\leq…

Statistics Theory · Mathematics 2017-03-03 Pierre Del Moral , Adrian N. Bishop

We compute analytically the probability distribution and moments of the sum and product of the non-zero eigenvalues and singular values of random matrices with (i) non-negative entries, (ii) fixed rank, and (iii) prescribed sums of the…

Statistical Mechanics · Physics 2025-06-17 Mark J. Crumpton , Yan V. Fyodorov , Pierpaolo Vivo

In descriptive statistics, $U$-statistics arise naturally in producing minimum-variance unbiased estimators. In 1984, Serfling considered the distribution formed by evaluating the kernel of the $U$-statistics and proposed generalized…

Statistics Theory · Mathematics 2024-09-13 Li Tuobang

We study limit distributions of independent random matrices as well as limit joint distributions of their blocks under normalized partial traces composed with classical expectation. In particular, we are concerned with the ensemble of…

Operator Algebras · Mathematics 2014-07-25 Romuald Lenczewski

In this paper, we prove a universality result of convergence for a bivariate random process defined by the eigenvectors of a sample covariance matrix. Let $V_n=(v_{ij})_{i \leq n,\, j\leq m}$ be a $n\times m$ random matrix, where $(n/m)\to…

Probability · Mathematics 2013-06-19 Ali Bouferroum

In this paper, we investigate certain combinatorial numbers, the \textit{moment generating Stirling numbers}. They are a special case of Hsu's generalized Stirling numbers and satisfy many more properties and combinatorial identities than…

Combinatorics · Mathematics 2022-06-20 Ludwig Frank

In this paper we consider ensemble of random matrices $\X_n$ with independent identically distributed vectors $(X_{ij}, X_{ji})_{i \neq j}$ of entries. Under assumption of finite fourth moment of matrix entries it is proved that empirical…

Probability · Mathematics 2012-08-07 Alexey Naumov

The joint moments of the derivatives of the characteristic polynomial of a random unitary matrix, and also a variant of the characteristic polynomial that is real on the unit circle, in the large matrix size limit, have been studied…

Probability · Mathematics 2024-10-16 Theodoros Assiotis , Mustafa Alper Gunes , Jonathan P. Keating , Fei Wei

The projected normal distribution, also known as the angular Gaussian distribution, is obtained by dividing a multivariate normal random variable $\mathbf{x}$ by its norm $\sqrt{\mathbf{x}^T \mathbf{x}}$. The resulting random variable…

Methodology · Statistics 2025-06-24 Daniel Herrera-Esposito , Johannes Burge

We study a class of random matrices that appear in several communication and signal processing applications, and whose asymptotic eigenvalue distribution is closely related to the reconstruction error of an irregularly sampled bandlimited…

Information Theory · Computer Science 2008-06-24 Alessandro Nordio , Carla-Fabiana Chiasserini , Emanuele Viterbo

We study asymptotic distributions of large dimensional random matrices of the form $BB^{*}$, where $B$ is a product of $p$ rectangular random matrices, using free probability and combinatorics of colored labeled noncrossing partitions.…

Probability · Mathematics 2020-04-03 Romuald Lenczewski , Rafał Sałapata

We investigate traces of powers of random matrices whose distributions are invariant under rotations (with respect to the Hilbert--Schmidt inner product) within a real-linear subspace of the space of $n\times n$ matrices. The matrices we…

Probability · Mathematics 2023-11-30 Elizabeth S. Meckes , Mark W. Meckes

We consider the following natural question. Given a matrix $A$ with i.i.d. random entries, what are the moments of the determinant of $A$? In other words, what is $\mathbb{E}[\det(A)^k]$? While there is a general expression for…

Combinatorics · Mathematics 2025-07-08 Dominik Beck , Zelin Lv , Aaron Potechin