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In this paper we analyze a greedy procedure to approximate a linear functional defined in a Reproducing Kernel Hilbert Space by nodal values. This procedure computes a quadrature rule which can be applied to general functionals, including…

Numerical Analysis · Mathematics 2021-05-19 Gabriele Santin , Toni Karvonen , Bernard Haasdonk

Kernel mean embeddings, a widely used technique in machine learning, map probability distributions to elements of a reproducing kernel Hilbert space (RKHS). For supervised learning problems, where input-output pairs are observed, the…

Machine Learning · Statistics 2024-10-24 Ambrus Tamás , Balázs Csanád Csáji

Reproducing kernel Hilbert spaces (RKHSs) are very important function spaces, playing an important role in machine learning, statistics, numerical analysis and pure mathematics. Since Lipschitz and H\"older continuity are important…

Functional Analysis · Mathematics 2023-10-30 Christian Fiedler

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

In this paper we consider the reproducing kernel thesis for boundedness and compactness for various operators on Bergman-type spaces. In particular, the results in this paper apply to the weighted Bergman space on the unit ball, the unit…

Complex Variables · Mathematics 2018-02-09 Mishko Mitkovski , Brett D. Wick

We consider the problem of learning a set from random samples. We show how relevant geometric and topological properties of a set can be studied analytically using concepts from the theory of reproducing kernel Hilbert spaces. A new kind of…

Machine Learning · Statistics 2014-11-26 Ernesto De Vito , Lorenzo Rosasco , Alessandro Toigo

Traditional functional linear regression usually takes a one-dimensional functional predictor as input and estimates the continuous coefficient function. Modern applications often generate two-dimensional covariates, which become matrices…

Methodology · Statistics 2024-11-26 Dan Yang , Jianlong Shao , Haipeng Shen , Hongtu Zhu

We characterize those generating functions k that produce weighted Hardy spaces of the unit disk D supporting nontrivial Hermitian weighted composition operators. Our characterization shows that the spaces associated with the "classical…

Functional Analysis · Mathematics 2011-04-08 Paul Bourdon , Wenling Shang

We study reproducing kernel Hilbert spaces (RKHS) on a Riemannian manifold. In particular, we discuss under which condition Sobolev spaces are RKHS and characterize their reproducing kernels. Further, we introduce and discuss a class of…

Functional Analysis · Mathematics 2019-05-28 Ernesto De Vito , Nicole Mücke , Lorenzo Rosasco

In this paper, we show that the approximation of high-dimensional functions, which are effectively low-dimensional, does not suffer from the curse of dimensionality. This is shown first in a general reproducing kernel Hilbert space set-up…

Numerical Analysis · Mathematics 2024-11-28 Christian Rieger , Holger Wendland

This paper introduces a directional multiscale algorithm for the two dimensional $N$-body problem of the Helmholtz kernel with applications to high frequency scattering. The algorithm follows the approach in [Engquist and Ying, SIAM Journal…

Numerical Analysis · Mathematics 2008-02-29 Björn Engquist , Lexing Ying

Since its introduction, the Discrete Variable Representation (DVR) basis set has become an invaluable representation of state vectors and Hermitian operators in non-relativistic quantum dynamics and spectroscopy calculations. On the other…

Computational Physics · Physics 2014-05-30 Hamse Mussa

Sub-Bergman Hilbert spaces are analogues of de Branges-Rovnyak spaces in the Bergman space setting. They are reproducing kernel Hilbert spaces contractively contained in the Bergman space of the unit disk. K. Zhu analyzed sub-Bergman…

Functional Analysis · Mathematics 2018-11-16 Cheng Chu

In this paper we study reproducing kernel Hilbert spaces of arbitrary smoothness on the sphere $\mathbb{S}^d \subset \mathbb{R}^{d+1}$. The reproducing kernel is given by an integral representation using the truncated power function…

Numerical Analysis · Mathematics 2014-02-17 J. Brauchart , J. Dick

In this paper, we define and study a nested family of reproducing kernel Hilbert spaces of vector fields that is indexed by a range of scales, from which we construct a reproducing kernel Hilbert space of scale-dependent vector fields. We…

Numerical Analysis · Mathematics 2025-01-09 Yechen Liu , Laurent Younes

Let $G$ be a locally compact abelian group with a Haar measure, and $Y$ be a measure space. Suppose that $H$ is a reproducing kernel Hilbert space of functions on $G\times Y$, such that $H$ is naturally embedded into $L^2(G\times Y)$ and is…

Functional Analysis · Mathematics 2025-04-28 Crispin Herrera-Yañez , Egor A. Maximenko , Gerardo Ramos-Vazquez

We do a preliminary study of the reproducing kernel Hilbert space having as kernel $k^d$, where $d$ is a positive integer and $k$ is the reproducing kernel of the analytic Dirichlet space.

Complex Variables · Mathematics 2016-05-19 Nicola Arcozzi , Karl-Mikael Perfekt , Pavel Mozolyako , Stefan Richter , Giulia Sarfatti

We consider frames F in a given Hilbert space, and we show that every F may be obtained in a constructive way from a reproducing kernel and an orthonormal basis in an ambient Hilbert space. The construction is operator-theoretic, building…

Classical Analysis and ODEs · Mathematics 2007-05-23 Palle E. T. Jorgensen

Let $\{v_n\}$ be a complete minimal system in a Hilbert space $\mathcal{H}$ and let $\{w_m\}$ be its biorthogonal system. It is well known that $\{w_m\}$ is not necessarily complete. However the situation may change if we consider systems…

Complex Variables · Mathematics 2011-12-26 Anton Baranov , Yurii Belov

The aim of this study is to present a good modernistic strategy for solving some well-known classes of Lane-Emden type singular differential equations. The proposed approach is based on the reproducing kernel Hilbert space (RKHS) and…

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