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In this paper, we study bounds of expected $L_2-$discrepancy to give mean square error of uniform integration approximation for functions in Sobolev space $\mathcal{H}^{\mathbf{1}}(K)$, where $\mathcal{H}$ is a reproducing Hilbert space…

Numerical Analysis · Mathematics 2021-10-05 Jun Xian , Xiaoda Xu

We analyze a new random algorithm for numerical integration of $d$-variate functions over $[0,1]^d$ from a weighted Sobolev space with dominating mixed smoothness $\alpha\ge 0$ and product weights $1\ge\gamma_1\ge\gamma_2\ge\cdots>0$, where…

Numerical Analysis · Mathematics 2019-08-15 Peter Kritzer , Frances Y. Kuo , Dirk Nuyens , Mario Ullrich

We consider $L^2$-approximation on weighted reproducing kernel Hilbert spaces of functions depending on infinitely many variables. We focus on unrestricted linear information, admitting evaluations of arbitrary continuous linear…

Numerical Analysis · Mathematics 2026-01-13 Kumar Harsha , Michael Gnewuch , Marcin Wnuk

Using tools from the theory of operator ideals and s-numbers, we develop a general approach to transfer estimates for $L_2$ -approximation of Sobolev functions into estimates for $L_\infty$-approximation, with precise control of all…

Functional Analysis · Mathematics 2015-05-12 Fernando Cobos , Thomas Kühn , Winfried Sickel

We consider the approximate recovery of multivariate periodic functions from a discrete set of function values taken on a rank-$s$ integration lattice. The main result is the fact that any (non-)linear reconstruction algorithm taking…

Numerical Analysis · Mathematics 2016-08-02 Glenn Byrenheid , Lutz Kämmerer , Tino Ullrich , Toni Volkmer

We examine the necessary and sufficient complexity of neural networks to approximate functions from different smoothness spaces under the restriction of encodable network weights. Based on an entropy argument, we start by proving lower…

Functional Analysis · Mathematics 2020-09-21 Ingo Gühring , Mones Raslan

A key problem in approximation theory is the recovery of high-dimensional functions from samples. In many cases, the functions of interest exhibit anisotropic smoothness, and, in many practical settings, the nature of this anisotropy may be…

Numerical Analysis · Mathematics 2026-04-10 Ben Adcock , Avi Gupta

We study quasi-Monte Carlo (QMC) methods for numerical integration of multivariate functions defined over the high-dimensional unit cube. Lattice rules and polynomial lattice rules, which are special classes of QMC methods, have been…

Numerical Analysis · Mathematics 2020-06-23 Josef Dick , Takashi Goda

We investigate the approximation of generalized Laguerre- or Laplace-weighted integrals over $\mathbb{R}^d_+$ or $\mathbb{R}^d$ of functions from generalized Laguerre- or Laplace-weighted Sobolev spaces of mixed smoothness, respectively. We…

Numerical Analysis · Mathematics 2025-12-29 Dinh Dũng

An algorithm is given for determining an optimal $b$-step approximation of weighted data, where the error is measured with respect to the $L_\infty$ norm. For data presorted by the independent variable the algorithm takes $\Theta(n + \log n…

Data Structures and Algorithms · Computer Science 2015-05-05 Quentin F. Stout

This paper considers the following question: how well can depth-two ReLU networks with randomly initialized bottom-level weights represent smooth functions? We give near-matching upper- and lower-bounds for $L_2$-approximation in terms of…

Machine Learning · Computer Science 2021-09-09 Daniel Hsu , Clayton Sanford , Rocco A. Servedio , Emmanouil-Vasileios Vlatakis-Gkaragkounis

We combine a periodization strategy for weighted $L_{2}$-integrands with efficient approximation methods in order to approximate multivariate non-periodic functions on the high-dimensional cube $\left[-\frac{1}{2},\frac{1}{2}\right]^{d}$.…

Numerical Analysis · Mathematics 2021-01-22 Robert Nasdala , Daniel Potts

We describe two quantum algorithms to approximate the mean value of a black-box function. The first algorithm is novel and asymptotically optimal while the second is a variation on an earlier algorithm due to Aharonov. Both algorithms have…

Quantum Physics · Physics 2011-06-22 Gilles Brassard , Frederic Dupuis , Sebastien Gambs , Alain Tapp

QMC rules are equal weight quadrature rules for approximating integrals over $[0,1]^s$. One line of research studies the integration error of functions in the unit ball of so-called Korobov spaces, which are Hilbert spaces of periodic…

Numerical Analysis · Mathematics 2014-11-12 Josef Dick , Peter Kritzer , Gunther Leobacher , Friedrich Pillichshammer

We investigate the approximation of weighted integrals over $\mathbb{R}^d$ for integrands from weighted Sobolev spaces of mixed smoothness. We prove upper and lower bounds of the convergence rate of optimal quadratures with respect to $n$…

Numerical Analysis · Mathematics 2023-05-01 Dinh Dũng

We study linear polynomial approximation of functions in weighted Sobolev spaces $W^r_{p,w}(\mathbb{R}^d)$ of mixed smoothness $r \in \mathbb{N}$, and their optimality in terms of Kolmogorov and linear $n$-widths of the unit ball…

Numerical Analysis · Mathematics 2025-01-03 Dinh Dũng

In previous work (Kuo, Nuyens, Wilkes, 2023), we showed that a lattice rule with a pre-determined generating vector but random number of points can achieve the near optimal convergence of $O(n^{-\alpha-1/2+\epsilon})$, $\epsilon > 0$, for…

Numerical Analysis · Mathematics 2024-01-02 Dirk Nuyens , Laurence Wilkes

This paper presents an approach for approximating the reachable space of robotic manipulators based on convex polytopes. The proposed approach predicts the reachable space over a given time horizon based on the robot's actuation limits and…

Computational Geometry · Computer Science 2022-12-01 Antun Skuric , Vincent Padois , David Daney

Consider the design based situation where an $r$-regular set is sampled on a random lattice. A fast algorithm for estimating the integrated mean curvature based on this observation is to use a weighted sum of $2\times \dotsm \times 2$…

Statistics Theory · Mathematics 2016-02-24 Anne Marie Svane

We consider multivariate $\mathbb{L}_2$-approximation in reproducing kernel Hilbert spaces which are tensor products of weighted Walsh spaces and weighted Korobov spaces. We study the minimal worst-case error…

Numerical Analysis · Mathematics 2017-01-12 Peter Kritzer , Helene Laimer , Friedrich Pillichshammer