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Even when neural networks are widely used in a large number of applications, they are still considered as black boxes and present some difficulties for dimensioning or evaluating their prediction error. This has led to an increasing…

Machine Learning · Statistics 2021-05-11 Pablo Morala , Jenny Alexandra Cifuentes , Rosa E. Lillo , Iñaki Ucar

This paper presents a novel method for polynomial approximation (Hermite approximation) using the fusion of value and derivative information. Therefore, the least-squares error in both domains is simultaneously minimized. A covariance…

Numerical Analysis · Mathematics 2019-03-27 Roland Ritt , Matthew Harker , Paul O'Leary

We study the monic polynomials orthogonal with respect to a symmetric perturbed Gaussian weight $$ w(x;t):=\mathrm{e}^{-x^2}\left(1+t\: x^2\right)^\lambda,\qquad x\in \mathbb{R}, $$ where $t> 0,\;\lambda\in \mathbb{R}$. This weight is…

Mathematical Physics · Physics 2023-08-21 Chao Min , Yang Chen

Shannon Entropy is the preeminent tool for measuring the level of uncertainty (and conversely, information content) in a random variable. In the field of communications, entropy can be used to express the information content of given…

Information Theory · Computer Science 2024-11-06 Bill Kay , Audun Myers , Thad Boydston , Emily Ellwein , Cameron Mackenzie , Iliana Alvarez , Erik Lentz

In this paper, we present explicit and computable error bounds for the asymptotic expansions of the Hermite polynomials with Plancherel--Rotach scale. Three cases, depending on whether the scaled variable lies in the outer or oscillatory…

Classical Analysis and ODEs · Mathematics 2021-11-16 Wei Shi , Gergő Nemes , Xiang-Sheng Wang , Roderick Wong

A Dirichlet polynomial $d$ in one variable ${\mathcal{y}}$ is a function of the form $d({\mathcal{y}})=a_n n^{\mathcal{y}}+\cdots+a_22^{\mathcal{y}}+a_11^{\mathcal{y}}+a_00^{\mathcal{y}}$ for some $n,a_0,\ldots,a_n\in\mathbb{N}$. We will…

Information Theory · Computer Science 2021-10-29 David I. Spivak , Timothy Hosgood

There has been significant interest in studying the asymptotics of certain generalised moments, called the moments of moments, of characteristic polynomials of random Haar-distributed unitary and symplectic matrices, as the matrix size $N$…

Mathematical Physics · Physics 2023-04-21 Theodoros Assiotis , Edward Eriksson , Wenqi Ni

We study the local properties of eigenvalues for the Hermite (Gaussian), Laguerre (Chiral) and Jacobi $\beta$-ensembles of $N\times N$ random matrices. More specifically, we calculate scaling limits of the expectation value of products of…

Mathematical Physics · Physics 2013-09-03 Patrick Desrosiers , Dang-Zheng Liu

This paper introduces a new idea for constructing operators associated with a certain class of probability measures. Special cases include several know classical and noncommutative probability. The main example is derived from Feller [30,…

Probability · Mathematics 2022-05-16 Wiktor Ejsmont

This paper is concerned with the asymptotic behavior of the generalized principal eigenvalues of elliptic operators and spreading speeds of Fisher-KPP equations in two-scale almost periodic media where one scale is fixed and another one…

Analysis of PDEs · Mathematics 2025-12-04 Xing Liang , Linfeng Xu , Tao Zhou

We obtain asymptotic counting results with error terms for complex orthospectrum for Schottky groups and orbit counting function for quadratic polynomials. Moreover, we prove equidistribution of holonomy associated to these dynamical…

Dynamical Systems · Mathematics 2018-11-14 Yan Mary He

In this paper we consider the problem of computing the likelihood of the profile of a discrete distribution, i.e., the probability of observing the multiset of element frequencies, and computing a profile maximum likelihood (PML)…

Data Structures and Algorithms · Computer Science 2020-04-07 Nima Anari , Moses Charikar , Kirankumar Shiragur , Aaron Sidford

Stochastic expansion-based methods of uncertainty quantification, such as polynomial chaos and separated representations, require basis functions orthogonal with respect to the density of random inputs. Many modern engineering problems…

Computation · Statistics 2018-08-06 Brandon A. Jones , Marc Balducci

We consider the smallest eigenvalue distributions of some Freud unitary ensembles, that is, the probabilities that all the eigenvalues of the Hermitian matrices from the ensembles lie in the interval $(t,\infty)$. This problem is related to…

Mathematical Physics · Physics 2024-02-26 Chao Min , Liwei Wang

We present exact modal expansions for photonic systems including highly dispersive media. The formulas, based on a simple version of the Keldysh theorem, are very general since both permeability and permittivity can be dispersive,…

Optics · Physics 2018-12-26 Frédéric Zolla , André Nicolet , Guillaume Demésy

We rewrite the recently proposed differential expansion formula for HOMFLY polynomials of the knot $4_1$ in arbitrary rectangular representation $R=[r^s]$ as a sum over all Young sub-diagrams $\lambda$ of $R$ with extraordinary simple…

High Energy Physics - Theory · Physics 2017-10-26 Ya. Kononov , A. Morozov

Given a compact parameter set $Y\subset R^p$, we consider polynomial optimization problems $(P_y$) on $R^n$ whose description depends on the parameter $y\inY$. We assume that one can compute all moments of some probability measure $\phi$ on…

Optimization and Control · Mathematics 2009-05-18 Jean B. Lasserre

Let $u(x)$ be a subpolynomial function in a Hardy field. We establish necessary and sufficient conditions for the weighted uniform distribution of the sequences $(u(n))_{n\in\mathbb{N}}$ and $(u(p_n))_{n\in\mathbb{N}}$, where $p_n$ denotes…

Number Theory · Mathematics 2025-09-25 Vitaly Bergelson , Grigori Kolesnik , Younghwan Son

On a probability space $(\Omega, \mathcal F, \mathbb P)$ we consider two independent sequences $(a_k)_{k \geq 1}$ and $(b_k)_{k \geq 1}$ of i.i.d. random variables that are centered with unit variance and which admit a moment strictly…

Probability · Mathematics 2019-12-23 Jürgen Angst , Guillaume Poly

Lately, a New Transmuted Logistic-exponential (NTLE) distribution was introduced and studied as an extension of the Logistic-Exponential Distribution (LED) with wider applicability in lifetime modelling. However, the maximum likelihood…