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Radial basis functions (RBFs) are prominent examples for reproducing kernels with associated reproducing kernel Hilbert spaces (RKHSs). The convergence theory for the kernel-based interpolation in that space is well understood and optimal…

Classical Analysis and ODEs · Mathematics 2023-09-15 Thomas Hangelbroek , Christian Rieger

We study the consistency of minimum-norm interpolation in reproducing kernel Hilbert spaces corresponding to bounded kernels. Our main result give lower bounds for the generalization error of the kernel interpolation measured in a…

Machine Learning · Statistics 2025-09-30 Yunfei Yang

Consider a non-negative, self-adjoint, maximally subelliptic operator on a compact manifold. We show that the spectral multiplier is a singular integral operator under an appropriate Mihlin-H\"ormander type condition. We establish the…

Functional Analysis · Mathematics 2025-01-13 Lingxiao Zhang

Classical convergence analysis for kernel interpolation typically assumes that the target function $f$ lies in the reproducing kernel Hilbert space $\mathcal{H}_k\!\left(\Omega\right)$ induced by a kernel on a domain…

Numerical Analysis · Mathematics 2025-12-09 Tobias Ehring , Max-Paul Vogel , Bernard Haasdonk

We present a similarity transformation theory based on a polynomial form of a particle-hole pair excitation operator. In the weakly correlated limit, this polynomial becomes an exponential, leading to coupled cluster doubles. In the…

Strongly Correlated Electrons · Physics 2016-11-23 Matthias Degroote , Thomas M. Henderson , Jinmo Zhao , Jorge Dukelsky , Gustavo E. Scuseria

This work provides theoretical foundations for kernel methods in the hyperspherical context. Specifically, we characterise the native spaces (reproducing kernel Hilbert spaces) and the Sobolev spaces associated with kernels defined over…

Machine Learning · Statistics 2022-11-18 Simon Hubbert , Emilio Porcu , Chris. J. Oates , Mark Girolami

We present an $\ell^2_2+\ell_1$-regularized discrete least squares approximation over general regions under assumptions of hyperinterpolation, named hybrid hyperinterpolation. Hybrid hyperinterpolation, using a soft thresholding operator…

Numerical Analysis · Mathematics 2024-07-08 Congpei An , Jiashu Ran , Alvise Sommariva

We study approximation of multivariate periodic functions from Besov and Triebel--Lizorkin spaces of dominating mixed smoothness by the Smolyak algorithm constructed using a special class of quasi-interpolation operators of…

Classical Analysis and ODEs · Mathematics 2021-08-27 Yurii Kolomoitsev

This paper focuses on scattered data fitting problems on spheres. We study the approximation performance of a class of weighted spectral filter algorithms, including Tikhonov regularization, Landaweber iteration, spectral cut-off, and…

Numerical Analysis · Mathematics 2024-10-24 Shao-Bo Lin

In this paper we propose a unified approach, based on limiting interpolation, to investigate the embeddings for the Sobolev space $(\dot{W}^k_p(\mathcal{X}))_0, \, \mathcal{X} \in \{\mathbb{R}^d, \mathbb{T}^d, \Omega\}$, in the subcritical…

Functional Analysis · Mathematics 2020-10-23 Oscar Domínguez , Sergey Tikhonov

The interpolation-regression approximation is a powerful tool in numerical analysis for reconstructing functions defined on square or triangular domains from their evaluations at a regular set of nodes. The importance of this technique lies…

Numerical Analysis · Mathematics 2025-08-12 Francesco Dell'Accio , Francisco Marcellán , Federico Nudo

It is an established fact that a finite difference operator approximates a derivative with a fixed algebraic rate of convergence. Nevertheless, we exhibit a new finite difference operator and prove it has spectral accuracy. Its rate of…

Numerical Analysis · Mathematics 2019-07-01 Andre Nachbin

These notes are devoted to various considerations on a family of sharp interpolation inequalities on the sphere, which in dimension two and higher interpolate between Poincar\'e, logarithmic Sobolev and critical Sobolev (Onofri in dimension…

Analysis of PDEs · Mathematics 2012-12-06 Jean Dolbeault , Maria J. Esteban , Michal Kowalczyk , Michael Loss

We develop a constructive piecewise polynomial approximation theory in weighted Sobolev spaces with Muckenhoupt weights for any polynomial degree. The main ingredients to derive optimal error estimates for an averaged Taylor polynomial are…

Numerical Analysis · Mathematics 2014-11-27 Ricardo H. Nochetto , Enrique Otarola , Abner J. Salgado

Regularizing a linear ill-posed operator equation can be achieved by manipulating the spectrum of the operator's pseudo-inverse. Tikhonov regularization and spectral cutoff are well-known techniques within this category. This paper…

Numerical Analysis · Mathematics 2026-02-11 Martin Sæbye Carøe , Mirza Karamehmedović , Pierre Maréchal

We adapt Schaback's error doubling trick [R. Schaback. Improved error bounds for scattered data interpolation by radial basis functions. Math. Comp., 68(225):201--216, 1999.] to give error estimates for radial interpolation of functions…

Numerical Analysis · Mathematics 2007-12-02 R. A. Brownlee , E. H. Georgoulis , J. Levesley

In this note, we present a well-known connection between the Sobolev-Slobodeckij spaces, also known as Fractional Sobolev spaces, and interpolation theory. We show how Sobolev spaces can be equivalently characterized as real and complex…

Functional Analysis · Mathematics 2025-09-19 Alberto Maione

We propose an extrapolation technique that allows accuracy improvement of the discrete dipole approximation computations. The performance of this technique was studied empirically based on extensive simulations for 5 test cases using many…

Optics · Physics 2008-07-29 Maxim A. Yurkin , Valeri P. Maltsev , Alfons G. Hoekstra

We derive $H_{\text{curl}}$-error estimates and improved $L^2$-error estimates for the Maxwell equations approximated using edge finite elements. These estimates only invoke the expected regularity pickup of the exact solution in the scale…

Numerical Analysis · Mathematics 2017-10-17 Alexandre Ern , Jean-Luc Guermond

We construct cubature methods on scattered data via resampling on the support of known algebraic cubature formulas, by different kinds of adaptive interpolation (polynomial, RBF, PUM). This approach gives a promising alternative to other…

Numerical Analysis · Mathematics 2023-07-17 R. Cavoretto , F. Dell'Accio , A. De Rossi , F. Di Tommaso , N. Siar , A. Sommariva , M. Vianello