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Derivative-matching approximations are constructed as power series built from functions. The method assumes the knowledge of special values of the Bell polynomials of the second kind, for which we refer to the literature. The presented…

General Mathematics · Mathematics 2022-11-28 Andrej Liptaj

We study the behaviour of the algebraic degree of vectorial Boolean functions when their inputs are restricted to an affine subspace of their domain. Functions which maintain their degree on all subspaces of as high a codimension as…

Commutative Algebra · Mathematics 2025-07-31 Claude Carlet , Serge Feukoua , Ana Salagean

The purpose of this note is to compare various approximation methods as applied to the inverse of the Bessel function of the first kind, in a given domain of the complex plane.

Numerical Analysis · Mathematics 2018-01-11 D. S. Karachalios , I. V. Gosea , Q. Zhang , A. C. Antoulas

We prove that the Newton product of efficient polynomial projectors is still efficient. Various polynomial approximation theorems are established involving Newton product projectors on spaces of holomorphic functions on a neighborhood of a…

Complex Variables · Mathematics 2021-03-24 François Bertrand , Jean-Paul Calvi

We consider approximation of functions of $s$ variables, where $s$ is very large or infinite, that belong to weighted anchored spaces. We study when such functions can be approximated by algorithms designed for functions with only very…

Numerical Analysis · Mathematics 2016-10-11 Peter Kritzer , Friedrich Pillichshammer , G. W. Wasilkowski

Consider an $s$-dimensional function being evaluated at $n$ points of a low discrepancy sequence (LDS), where the objective is to approximate the one-dimensional functions that result from integrating out $(s-1)$ variables. Here, the…

Numerical Analysis · Mathematics 2019-11-11 Chaitanya Joshi , Paul T. Brown , Stephen Joe

It is often useful to have polynomial upper or lower bounds on a one-dimensional function that are valid over a finite interval, called a trust region. A classical way to produce polynomial bounds of degree $k$ involves bounding the range…

Numerical Analysis · Mathematics 2023-08-24 Matthew Streeter , Joshua V. Dillon

The aim of this paper is twofold. Firstly, we give easy-to-handle criteria to determine whether a given family of subsets of a vector space is a neighbourhood basis of the origin for a complete vector topology. Then, we apply these criteria…

Functional Analysis · Mathematics 2025-02-20 José L. Ansorena , Alejandro Marcos

We study the polynomial approximation of symmetric multivariate functions and of multi-set functions. Specifically, we consider $f(x_1, \dots, x_N)$, where $x_i \in \mathbb{R}^d$, and $f$ is invariant under permutations of its $N$…

Numerical Analysis · Mathematics 2023-02-06 Markus Bachmayr , Geneviève Dusson , Christoph Ortner , Jack Thomas

Motivated by numerical methods for solving parametric partial differential equations, this paper studies the approximation of multivariate analytic functions by algebraic polynomials. We introduce various anisotropic model classes based on…

Numerical Analysis · Mathematics 2020-01-17 Andrea Bonito , Ronald DeVore , Diane Guignard , Peter Jantsch , Guergana Petrova

Approximation by polynomials on a triangle is studied in the Sobolev space $W_2^r$ that consists of functions whose derivatives of up to $r$-th order have bounded $L^2$ norm. The first part aims at understanding the orthogonal structure in…

Classical Analysis and ODEs · Mathematics 2017-04-18 Yuan Xu

A fundamental problem in numerical analysis and approximation theory is approximating smooth functions by polynomials. A much harder version under recent consideration is to enforce bounds constraints on the approximating polynomial. In…

Numerical Analysis · Mathematics 2021-12-28 Larry Allen , Robert C. Kirby

In this paper we develop a new machinery to study the capacity of artificial neural networks (ANNs) to approximate high-dimensional functions without suffering from the curse of dimensionality. Specifically, we introduce a concept which we…

Numerical Analysis · Mathematics 2025-01-29 Pierfrancesco Beneventano , Patrick Cheridito , Arnulf Jentzen , Philippe von Wurstemberger

Polynomial approximation is studied in the Sobolev space $W_p^r(w_{\alpha,\beta})$ that consists of functions whose $r$-th derivatives are in weighted $L^p$ space with the Jacobi weight function $w_{\alpha,\beta}$. This requires…

Classical Analysis and ODEs · Mathematics 2017-11-01 Yuan Xu

We consider properties of the box polynomials, a one variable polynomial defined over all integer partitions $\lambda$ whose Young diagrams fit in an $m$ by $n$ box. We show that these polynomials can be expressed by the finite difference…

Combinatorics · Mathematics 2017-09-01 Richard Ehrenborg , Alex Happ , Dustin Hedmark , Cyrus Hettle

This paper presents a novel method for generating a single polynomial approximation that produces correctly rounded results for all inputs of an elementary function for multiple representations. The generated polynomial approximation has…

Mathematical Software · Computer Science 2022-03-18 Mridul Aanjaneya , Jay P. Lim , Santosh Nagarakatte

This paper extends the universal approximation property of single-hidden-layer feedforward neural networks beyond compact domains, which is of particular interest for the approximation within weighted $C^k$-spaces and weighted Sobolev…

Machine Learning · Statistics 2025-07-08 Ariel Neufeld , Philipp Schmocker

We generalize a version of Lavrent\'ev's theorem which says that a function that is continuous on a compact set K with connected complement and without interior points can be uniformly approximated as closely as desired by a polynomial…

Complex Variables · Mathematics 2019-07-02 Johan Andersson , Linnea Rousu

We discuss the Siciak-Zaharjuta extremal function of pluripotential theory for the unit ball in C^d for spaces of polynomials with the notion of degree determined by a convex body P. We then use it to analyze the approximation properties of…

Complex Variables · Mathematics 2018-01-09 T. Bloom , L. Bos , N. Levenberg , S. Ma'u , F. Piazzon

Matrix functions are a central topic of linear algebra, and problems requiring their numerical approximation appear increasingly often in scientific computing. We review various limited-memory methods for the approximation of the action of…

Numerical Analysis · Mathematics 2020-10-26 Stefan Güttel , Daniel Kressner , Kathryn Lund