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We establish presumably optimal rates of normal convergence with respect to the Kolmogorov distance for a large class of geometric functionals of marked Poisson and binomial point processes on general metric spaces. The rates are valid…

Probability · Mathematics 2017-02-03 Raphaël Lachièze-Rey , Matthias Schulte , J. E. Yukich

Functions with discontinuities appear in many applications such as image reconstruction, signal processing, optimal control problems, interface problems, engineering applications and so on. Accurate approximation and interpolation of these…

Numerical Analysis · Mathematics 2023-02-07 Mohammad Karimnejad Esfahani , Stefano De Marchi , Francesco Marchetti

In this article we prove that it is possible to construct, using newest-vertex bisection, meshes that equidistribute the error in $H^1$-norm, whenever the function to approximate can be decomposed as a sum of a regular part plus a singular…

Numerical Analysis · Mathematics 2008-03-28 Fernando D. Gaspoz , Pedro Morin

This paper deals with the \emph{integral} version of the Dirichlet homogeneous fractional Laplace equation. For this problem weighted and fractional Sobolev a priori estimates are provided in terms of the H\"older regularity of the data. By…

Numerical Analysis · Mathematics 2017-01-11 Gabriel Acosta , Juan Pablo Borthagaray

In this paper, we introduce a new theoretical framework built upon fractional Sobolev-type spaces involving Riemann-Liouville (RL) fractional integrals/derivatives, which is naturally arisen from exact representations of Chebyshev expansion…

Numerical Analysis · Mathematics 2019-05-28 Wenjie Liu , Li-Lian Wang , Huiyuan Li

In this paper we consider the approximation of a function by its interpolating multilinear spline and the approximation of its derivatives by the derivatives of the corresponding spline. We derive formulas for the uniform approximation…

Numerical Analysis · Mathematics 2013-08-27 Ryan Anderson , Yuliya Babenko , Tetiana Leskevych

We prove a.s. (almost sure) unisolvency of interpolation by continuous random sampling with respect to any given density, in spaces of multivariate a.e. (almost everywhere) analytic functions. Examples are given concerning polynomial and…

Numerical Analysis · Mathematics 2023-03-27 Francesco Dell'Accio , Alvise Sommariva , Marco Vianello

On the sets of $2\pi$-periodic functions $f$, which are defined with a help of $(\psi, \beta)$-integrals of the functions $\varphi$ from $L_{1}$, we establish Lebesgue-type inequalities, in which the uniform norms of deviations of Fourier…

Classical Analysis and ODEs · Mathematics 2023-01-06 Anatoly Serdyuk , Tetiana Stepaniuk

We prove that two fixed univariate functions, namely, an arbitrary continuous non-affine function and a concrete affine function, are sufficient to approximate continuous functions of one variable under the operations of addition and…

Functional Analysis · Mathematics 2026-05-27 Vugar Ismailov

We propose novel methods for approximate sampling recovery and integration of functions in the Freud-weighted Sobolev space $W^r_{p,w}(\mathbb{R})$. The approximation error of sampling recovery is measured in the norm of the Freud-weighted…

Numerical Analysis · Mathematics 2026-01-06 Dinh Dũng

This paper proves that the approximation of pointwise derivatives of order $s$ of functions in Sobolev space $W_2^m(\R^d)$ by linear combinations of function values cannot have a convergence rate better than $m-s-d/2$, no matter how many…

Numerical Analysis · Mathematics 2016-11-16 Oleg Davydov , Robert Schaback

Adaptive spectral (AS) decompositions associated with a piecewise constant function $u$ yield small subspaces where the characteristic functions comprising $u$ are well approximated. When combined with Newton-like optimization methods for…

Numerical Analysis · Mathematics 2022-07-05 Daniel H. Baffet , Yannik G. Gleichmann , Marcus J. Grote

Probabilistic graphical models are a key tool in machine learning applications. Computing the partition function, i.e., normalizing constant, is a fundamental task of statistical inference but it is generally computationally intractable,…

Machine Learning · Statistics 2020-01-29 Sungsoo Ahn , Michael Chertkov , Adrian Weller , Jinwoo Shin

We propose a general algorithm for approximating nonstandard Bayesian posterior distributions. The algorithm minimizes the Kullback-Leibler divergence of an approximating distribution to the intractable posterior distribution. Our method…

Computation · Statistics 2014-07-29 Tim Salimans , David A. Knowles

The approximate degree of a Boolean function $f \colon \{-1, 1\}^n \rightarrow \{-1, 1\}$ is the least degree of a real polynomial that approximates $f$ pointwise to error at most $1/3$. We introduce a generic method for increasing the…

Computational Complexity · Computer Science 2017-03-20 Mark Bun , Justin Thaler

We investigate the problem of fitting piecewise affine functions (PWA) to data. Our algorithm divides the input domain into finitely many polyhedral regions whose shapes are specified using a user-defined template such that the data points…

Systems and Control · Electrical Eng. & Systems 2024-11-20 Guillaume O. Berger , Sriram Sankaranarayanan

We introduce an adaptation of integral approximation operators to set-valued functions (SVFs, multifunctions), mapping a compact interval $[a,b]$ into the space of compact non-empty subsets of ${\mathbb R}^d$. All operators are adapted by…

Classical Analysis and ODEs · Mathematics 2022-12-02 Elena E. Berdysheva , Nira Dyn , Elza Farkhi , Alona Mokhov

Any continuous piecewise-linear function $F\colon \mathbb{R}^{n}\to \mathbb{R}$ can be represented as a linear combination of $\max$ functions of at most $n+1$ affine-linear functions. In our previous paper [``Representing piecewise linear…

Discrete Mathematics · Computer Science 2024-06-05 Christoph Koutschan , Anton Ponomarchuk , Josef Schicho

In this paper, we prove sharp upper and lower bounds for the approximation of Sobolev functions by sums of multivariate ridge functions, i.e., for approximation by functions of the form $\mathbb{R}^d \ni x \mapsto \sum_{k=1}^n \varrho_k(A_k…

Functional Analysis · Mathematics 2025-07-02 Paul Geuchen , Palina Salanevich , Olov Schavemaker , Felix Voigtlaender

We prove a Leibniz rule for BV functions in a complete metric space that is equipped with a doubling measure and supports a Poincar\'e inequality. Unlike in previous versions of the rule, we do not assume the functions to be locally…

Metric Geometry · Mathematics 2018-11-20 Panu Lahti