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Related papers: Nevanlinna-Pick Kernels and Localization

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We consider positive semidefinite kernels which have values given by bounded linear operators on certain bundles of Hilbert spaces and which are invariant under actions of $*$-semigroupoids. For these kernels, we prove that there exist…

Functional Analysis · Mathematics 2026-02-20 Aurelian Gheondea

Suppose H is a space of functions on X. If H is a Hilbert space with reproducing kernel then that structure of H can be used to build distance functions on X. We describe some of those and their interpretations and interrelations. We also…

Complex Variables · Mathematics 2012-05-01 Nicola Arcozzi , Richard Rochberg , Eric T. Sawyer , Brett D. Wick

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 work, we consider the problem of learning nonlinear operators that correspond to discrete-time nonlinear dynamical systems with inputs. Given an initial state and a finite input trajectory, such operators yield a finite output…

Optimization and Control · Mathematics 2024-12-25 Mircea Lazar

We prove a characterization for the Peetre type $K$-functional on $\mathbb{M}$, a compact two-point homogeneous space, in terms the rate of approximation of a family of multipliers operator defined to this purpose. This extends the well…

Functional Analysis · Mathematics 2018-06-25 A. O. Carrijo , T. Jordão

Reproducing kernel Hilbert spaces are elucidated without assuming prior familiarity with Hilbert spaces. Compared with extant pedagogic material, greater care is placed on motivating the definition of reproducing kernel Hilbert spaces and…

History and Overview · Mathematics 2015-11-06 Jonathan H. Manton , Pierre-Olivier Amblard

We show that sampling or interpolation formulas in reproducing kernel Hilbert spaces can be obtained by reproducing kernels whose dual systems form molecules, ensuring that the size profile of a function is fully reflected by the size…

Functional Analysis · Mathematics 2022-05-04 José Luis Romero , Jordy Timo van Velthoven , Felix Voigtlaender

This paper is devoted to the study of reproducing kernel Hilbert spaces. We focus on multipliers of reproducing kernel Banach and Hilbert spaces. In particular we tried to extend this concept and prove some theorems.

Functional Analysis · Mathematics 2016-01-07 Ali Ebadian , Saeed Hashemi Sababe , Maysam Zallaghi

Kernel theorems, in general, provide a convenient representation of bounded linear operators. For the operator acting on a concrete function space, this means that its action on any element of the space can be expressed as a generalised…

Functional Analysis · Mathematics 2024-05-22 Dimitri Bytchenkoff , Michael Speckbacher , Peter Balazs

We study embeddings between reproducing kernel Hilbert spaces $H(K)$ of functions of $d \in \mathbb{N} \cup \{\infty\}$ variables. The kernels $K$ are superpositions of weighted finite tensor products of a fixed univariate kernel. The basic…

Numerical Analysis · Mathematics 2026-05-01 Michael Gnewuch , Peter Kritzer , Klaus Ritter

The purpose of this article is to construct highly localized summability kernels on the unit sphere in ${\mathbb R}^d$ that are restrictions to the sphere of linear combinations of a small number of shifts of the fundamental solution of the…

Classical Analysis and ODEs · Mathematics 2018-08-28 Kamen Ivanov , Pencho Petrushev

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

With view to applications in stochastic analysis and geometry, we introduce a new correspondence for positive definite kernels (p.d.) $K$ and their associated reproducing kernel Hilbert spaces. With this we establish two kinds of…

Functional Analysis · Mathematics 2019-11-28 Palle Jorgensen , Feng Tian

We consider reproducing kernel Hilbert spaces of Dirichlet series with kernels of the form $k(s,u) = \sum a_n n^{-s-\bar u}$, and characterize when such a space is a complete Pick space. We then discuss what it means for two reproducing…

Functional Analysis · Mathematics 2025-04-15 John E. McCarthy , Orr Shalit

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 present decompositions of various positive kernels as integrals or sums of positive kernels. Within this framework we study the reproducing kernel Hilbert spaces associated with the fractional and bi-fractional Brownian motions. As a…

Probability · Mathematics 2007-05-23 Daniel Alpay , David Levanony

In this paper we introduce reproducing kernel Hilbert spaces of polyanalytic functions of infinite order. First we study in details the counterpart of the Fock space and related results in this framework. In this case the kernel function is…

Complex Variables · Mathematics 2021-12-30 Daniel Alpay , Fabrizio Colombo , Kamal Diki , Irene Sabadini

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

Let $\mathcal H$ be a reproducing kernel Hilbert space with a normalized complete Nevanlinna-Pick (CNP) kernel. We prove that if $(f_n)$ is a sequence of functions in $\mathcal H$ with $\sum\|f_n\|^2<\infty$, then there exists a contractive…

Functional Analysis · Mathematics 2018-11-28 Michael T. Jury , Robert T. W. Martin

We review machine learning methods employing positive definite kernels. These methods formulate learning and estimation problems in a reproducing kernel Hilbert space (RKHS) of functions defined on the data domain, expanded in terms of a…

Statistics Theory · Mathematics 2009-09-29 Thomas Hofmann , Bernhard Schölkopf , Alexander J. Smola
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