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We introduce a family of reproducing kernel Hilbert spaces $\mathcal A_\Lambda$ of holomorphic functions defined on an infinite--dimensional domain in a separable Hilbert space, $\mathbb{H}$. The reproducing kernel of $\mathcal A_\Lambda$…

Mathematical Physics · Physics 2026-05-05 Dimitrios Giannakis , Mohammad Javad Latifi Jebelli , Michael Montgomery

Based on direct integrals, a framework allowing to integrate a parametrised family of reproducing kernels with respect to some measure on the parameter space is developed. By pointwise integration, one obtains again a reproducing kernel…

Functional Analysis · Mathematics 2012-02-21 Thomas Hotz , Fabian J. E. Telschow

We develop novel learning rates for conditional mean embeddings by applying the theory of interpolation for reproducing kernel Hilbert spaces (RKHS). We derive explicit, adaptive convergence rates for the sample estimator under the…

Machine Learning · Statistics 2026-04-09 Prem Talwai , Ali Shameli , David Simchi-Levi

We develop a comprehensive framework for spatio-temporal prediction of time-varying vector fields using operator-valued reproducing kernel Hilbert spaces (OV RKHS). By integrating Sobolev regularity with Koopman operator theory, we…

General Mathematics · Mathematics 2026-05-12 Mahishanka Withanachchi

Recently it has been shown that any regular simple symmetric operator with deficiency indices (1,1) is unitarily equivalent to the operator of multiplication in a reproducing kernel Hilbert space of functions on the real line with the…

Functional Analysis · Mathematics 2009-09-14 R. T. W. Martin

A mathematical model for variable selection in functional regression models with scalar response is proposed. By "variable selection" we mean a procedure to replace the whole trajectories of the functional explanatory variables with their…

Methodology · Statistics 2017-04-21 José R. Berrendero , Beatriz Bueno-Larraz , Antonio Cuevas

The structure of certain types of quasi shift-invariant spaces, which take the form $V(\psi,\mathcal{X}):=\overline{\text{span}}^{L_2}\{\psi(\cdot-x_j):j\in\mathbb{Z}\}$ for a discrete set $\mathcal{X}=(x_j)\subset\mathbb{R}$ is…

Functional Analysis · Mathematics 2018-02-14 Keaton Hamm , Jeff Ledford

Given a LHS (Lattice of Hilbert spaces) $V_J$ and a symmetric operator $A$ in $V_J$, in the sense of partial inner product spaces, we define a generalized resolvent for $A$ and study the corresponding spectral properties. In particular, we…

Mathematical Physics · Physics 2016-10-24 Jean-Pierre Antoine , Camillo Trapani

This paper deals with certain aspects of the vector valued de Branges spaces of entire functions that are based on pairs of Fredholm operator valued functions. Some factorization and isometric embedding results are extended from the scalar…

Functional Analysis · Mathematics 2026-04-08 Subhankar Mahapatra , Santanu Sarkar

The integral of the Wigner function of a quantum mechanical system over a region or its boundary in the classical phase plane, is called a quasiprobability integral. Unlike a true probability integral, its value may lie outside the interval…

Quantum Physics · Physics 2009-11-10 A. J. Bracken , D. Ellinas , J. G. Wood

This paper presents a framework for computing random operator-valued feature maps for operator-valued positive definite kernels. This is a generalization of the random Fourier features for scalar-valued kernels to the operator-valued case.…

Machine Learning · Computer Science 2016-08-22 Ha Quang Minh

Devoted to multi-task learning and structured output learning, operator-valued kernels provide a flexible tool to build vector-valued functions in the context of Reproducing Kernel Hilbert Spaces. To scale up these methods, we extend the…

Machine Learning · Computer Science 2018-05-25 Romain Brault , Florence d'Alché-Buc , Markus Heinonen

We establish the asymptotic normality of the kernel type estimator for the regression function constructed from quasi-associated data when the explanatory variable takes its values in a separable Hilbert space.

Statistics Theory · Mathematics 2018-05-08 Lahcen Douge

This paper studies the construction of a refinement kernel for a given operator-valued reproducing kernel such that the vector-valued reproducing kernel Hilbert space of the refinement kernel contains that of the given one as a subspace.…

Machine Learning · Computer Science 2011-02-08 Yuesheng Xu , Haizhang Zhang , Qinghui Zhang

We obtain sampling and interpolation theorems in radial weighted spaces of analytic functions for weights of arbitrary (more rapid than polynomial) growth. We give an application to invariant subspaces of arbitrary index in large weighted…

Complex Variables · Mathematics 2007-05-23 A. Borichev , R. Dhuez , K. Kellay

This article describes Hilbert spaces contractively contained in certain reproducing kernel Hilbert spaces of analytic functions on the open unit disc which are nearly invariant under division by an inner function. We extend Hitt's theorem…

Functional Analysis · Mathematics 2025-02-19 Arshad Khan , Sneh Lata , Dinesh Singh

The X-ray transform is one of the most fundamental integral operators in image processing and reconstruction. In this article, we revisit the formalism of the X-ray transform by considering it as an operator between Reproducing Kernel…

Functional Analysis · Mathematics 2024-06-26 Ho Yun , Victor M. Panaretos

We study approximation properties of general multivariate periodic quasi-interpolation operators, which are generated by distributions/functions $\widetilde{\varphi}_j$ and trigonometric polynomials $\varphi_j$. The class of such operators…

Classical Analysis and ODEs · Mathematics 2021-07-27 Yurii Kolomoitsev , Jürgen Prestin

We demonstrate an equivalence between reproducing kernel Hilbert space (RKHS) embeddings of conditional distributions and vector-valued regressors. This connection introduces a natural regularized loss function which the RKHS embeddings…

Machine Learning · Computer Science 2012-07-25 Steffen Grünewälder , Guy Lever , Luca Baldassarre , Sam Patterson , Arthur Gretton , Massimilano Pontil

Spline quasi-interpolation (QI) is a general and powerful approach for the construction of low cost and accurate approximations of a given function. In order to provide an efficient adaptive approximation scheme in the bivariate setting, we…

Numerical Analysis · Mathematics 2016-02-05 Cesare Bracco , Carlotta Giannelli , Francesca Mazzia , Alessandra Sestini