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In statistical learning theory, interpolation spaces of the form $[\mathrm{L}^2,H]_{\theta,r}$, where $H$ is a reproducing kernel Hilbert space, are in widespread use. So far, however, they are only well understood for fine index $r=2$. We…

Functional Analysis · Mathematics 2025-12-23 Michael Bitzer , Ingo Steinwart

We study multivariate integration and approximation for functions belonging to a weighted reproducing kernel Hilbert space based on half-period cosine functions in the worst-case setting. The weights in the norm of the function space depend…

Numerical Analysis · Mathematics 2015-11-23 Christian Irrgeher , Peter Kritzer , Friedrich Pillichshammer

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

Much recent work has addressed the solution of a family of partial differential equations by computing the inverse operator map between the input and solution space. Toward this end, we incorporate function-valued reproducing kernel Hilbert…

Numerical Analysis · Mathematics 2022-04-05 Kaijun Bao , Xu Qian , Ziyuan Liu , Songhe Song

Positive definite kernels and their associated Reproducing Kernel Hilbert Spaces provide a mathematically compelling and practically competitive framework for learning from data. In this paper we take the approximation theory point of view…

Machine Learning · Computer Science 2018-08-06 Mikhail Belkin

We show that polynomials do not belong to the reproducing kernel Hilbert space of infinitely differentiable translation-invariant kernels whose spectral measures have moments corresponding to a determinate moment problem. Our proof is based…

Statistics Theory · Mathematics 2021-08-13 Holger Dette , Anatoly Zhigljavsky

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

Kernel methods have been widely applied to machine learning and other questions of approximating an unknown function from its finite sample data. To ensure arbitrary accuracy of such approximation, various denseness conditions are imposed…

Machine Learning · Statistics 2013-10-25 Benxun Wang , Haizhang Zhang

We investigate the interaction between the existence of reproducing kernels on infinite-dimensional Hermitian vector bundles and the positivity properties of the corresponding bundles. The positivity refers to the curvature form of certain…

Functional Analysis · Mathematics 2014-02-04 Daniel Beltita , José E. Galé

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

Kernel interpolation is a fundamental technique for approximating functions from scattered data, with a well-understood convergence theory when interpolating elements of a reproducing kernel Hilbert space. Beyond this classical setting,…

Numerical Analysis · Mathematics 2025-05-19 Toni Karvonen , Gabriele Santin , Tizian Wenzel

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

In this paper we investigate the problem of estimating the regression function in models with correlated observations. The data is obtained from several experimental units each of them forms a time series. We propose a new estimator based…

Statistics Theory · Mathematics 2019-06-13 Djihad Benelmadani , Karim Benhenni , Sana Louhichi

Hilbertian kernel methods and their positive semidefinite kernels have been extensively used in various fields of applied mathematics and machine learning, owing to their several equivalent characterizations. We here unveil an analogy with…

Functional Analysis · Mathematics 2023-01-10 Pierre-Cyril Aubin-Frankowski , Stéphane Gaubert

We review definitions and properties of reproducing kernel Hilbert spaces attached to Gaussian variables and processes, with a view to applications in nonparametric Bayesian statistics using Gaussian priors. The rate of contraction of…

Functional Analysis · Mathematics 2008-12-18 A. W. van der Vaart , J. H. van Zanten

In this note we prove that the reproducing kernel of a Hilbert space satisfying the division property has integrable form, is locally of trace class, and the Hilbert space itself is a Hilbert space of holomorphic functions.

Functional Analysis · Mathematics 2018-12-10 Alexander I. Bufetov , Roman V. Romanov

We continue our earlier investigation on generalized reproducing kernels, in connection with the complex geometry of $C^*$- algebra representations, by looking at them as the objects of an appropriate category. Thus the correspondence…

Operator Algebras · Mathematics 2009-12-02 Daniel Beltita , Jose E. Gale

In this paper we study the relationships between a reproducing kernel Hilbert space, its multiplier algebra, and the geometry of the point set on which they live. We introduce a variant of the Banach-Mazur distance suited for measuring the…

Functional Analysis · Mathematics 2025-04-15 Danny Ofek , Satish K. Pandey , Orr Shalit

We study reproducing kernels, and associated reproducing kernel Hilbert spaces (RKHSs) $\mathscr{H}$ over infinite, discrete and countable sets $V$. In this setting we analyze in detail the distributions of the corresponding Dirac…

Functional Analysis · Mathematics 2015-01-13 Palle Jorgensen , Feng Tian

Herein, the theory of Bergman kernel is developed to the weighted case. A general form of weighted Bergman reproducing kernel is obtained, by which we can calculate concrete Bergman kernel functions for specific weights and domains.

Complex Variables · Mathematics 2020-09-08 Guan-Tie Deng , Yun Huang , Tao Qian