Near-Optimal Sampling Strategies for Multivariate Function Approximation on General Domains
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Publication:5037568
DOI10.1137/19M1279459zbMath1484.41015arXiv1908.01249OpenAlexW3043414797MaRDI QIDQ5037568
Publication date: 1 March 2022
Published in: SIAM Journal on Mathematics of Data Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1908.01249
Monte Carlo methods (65C05) Inequalities in approximation (Bernstein, Jackson, Nikol'ski?-type inequalities) (41A17) Multidimensional problems (41A63) Approximation by polynomials (41A10)
Related Items (9)
An Adaptive Sampling and Domain Learning Strategy for Multivariate Function Approximation on Unknown Domains ⋮ On the fractional calculus of multivariate Mittag-Leffler functions ⋮ Optimal sampling and Christoffel functions on general domains ⋮ A Stieltjes Algorithm for Generating Multivariate Orthogonal Polynomials ⋮ APPROXIMATING SMOOTH, MULTIVARIATE FUNCTIONS ON IRREGULAR DOMAINS ⋮ Random sampling and unisolvent interpolation by almost everywhere analytic functions ⋮ Towards optimal sampling for learning sparse approximation in high dimensions ⋮ Optimal pointwise sampling for \(L^2\) approximation ⋮ CAS4DL: Christoffel adaptive sampling for function approximation via deep learning
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