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Related papers: An Operator Theoretical Approach to Mercer's Theor…

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The universality properties of kernels characterize the class of functions that can be approximated in the associated reproducing kernel Hilbert space and are of fundamental importance in the theoretical underpinning of kernel methods in…

Machine Learning · Computer Science 2025-06-25 Franziskus Steinert , Salem Said , Cyrus Mostajeran

The classical Mercer's theorem claims that a continuous positive definite kernel $K({\mathbf x}, {\mathbf y})$ on a compact set can be represented as $\sum_{i=1}^\infty \lambda_i\phi_i({\mathbf x})\phi_i({\mathbf y})$ where…

Machine Learning · Computer Science 2022-09-27 Rustem Takhanov

In this paper, we characterize the families of those bounded linear operators on a separable Hilbert space which are simultaneously unitarily equivalent to integral bi-Carleman operators on $L_2(R)$ having arbitrarily smooth kernels of…

Spectral Theory · Mathematics 2007-05-23 Igor M. Novitskii

We study the spectral theory of operators, generated as direct sums of self-adjoint extensions of quasi-differential minimal operators on a multi-interval set (self-adjoint vector-operators), acting in a Hilbert space. Spectral theorems for…

Spectral Theory · Mathematics 2007-05-23 Maksim Sokolov

We start by showing how to approximate unitary and bounded self-adjoint operators by operators in finite dimensional spaces. Using ultraproducts we give a precise meaning for the approximation. In this process we see how the spectral…

Logic · Mathematics 2022-08-16 Åsa Hirvonen , Tapani Hyttinen

The theme of this work is that the theory of charged particles in a uniform magnetic field can be generalized to a large class of operators if one uses an extended a class of Weyl operators which we call "Landau--Weyl pseudodifferential…

Mathematical Physics · Physics 2008-10-22 Maurice de Gosson , Franz Luef

Traditional machine learning models, particularly neural networks, are rooted in finite-dimensional parameter spaces and nonlinear function approximations. This report explores an alternative formulation where learning tasks are expressed…

Machine Learning · Computer Science 2025-07-30 Andrew Kiruluta , Andreas Lemos , Priscilla Burity

In this paper we consider the problems of supervised classification and regression in the case where attributes and labels are functions: a data is represented by a set of functions, and the label is also a function. We focus on the use of…

Machine Learning · Computer Science 2016-11-03 Hachem Kadri , Emmanuel Duflos , Philippe Preux , Stéphane Canu , Alain Rakotomamonjy , Julien Audiffren

A weighted composition operator on a reproducing kernel Hilbert space is given by a composition, followed by a multiplication. We study unitary and co-isometric weighted composition operators on unitarily invariant spaces on the Euclidean…

Functional Analysis · Mathematics 2025-12-23 Michael Hartz , Maximilian Tornes

Transfer operators such as the Perron--Frobenius or Koopman operator play an important role in the global analysis of complex dynamical systems. The eigenfunctions of these operators can be used to detect metastable sets, to project the…

Dynamical Systems · Mathematics 2019-12-02 Stefan Klus , Ingmar Schuster , Krikamol Muandet

Motivated by the need of processing functional-valued data, or more general, operatorvalued data, we introduce the notion of the operator reproducing kernel Hilbert space (ORKHS). This space admits a unique operator reproducing kernel which…

Functional Analysis · Mathematics 2016-10-23 Rui Wang , Yuesheng Xu

This monograph develops a unified, application-driven framework for kernel methods grounded in reproducing kernel Hilbert spaces (RKHS) and optimal transport (OT). Part I lays the theoretical and numerical foundations on positive-definite…

Numerical Analysis · Mathematics 2025-10-07 Philippe G. LeFloch , Jean-Marc Mercier , Shohruh Miryusupov

In many instances one has to deal with parametric models. Such models in vector spaces are connected to a linear map. The reproducing kernel Hilbert space and affine- / linear- representations in terms of tensor products are directly…

Numerical Analysis · Mathematics 2018-11-26 Hermann G. Matthies , Roger Ohayon

In this paper we consider the problem of approximating vector-valued functions over a domain $\Omega$. For this purpose, we use matrix-valued reproducing kernels, which can be related to Reproducing kernel Hilbert spaces of vectorial…

Numerical Analysis · Mathematics 2019-01-11 Dominik Wittwar , Gabriele Santin , Bernard Haasdonk

In this work, a connection between some spectral properties of direct integral of operators in the direct integral of Hilbert spaces and their coordinate operators has been investigated.

Functional Analysis · Mathematics 2011-12-13 Z. I. Ismailov , E. Otkun Cevik

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

This paper is devoted to self-adjoint cyclically compact operators on Hilbert--Kaplansky module over a ring of bounded measurable functions. The spectral theorem for such a class of operators are given. We apply this result to partial…

Operator Algebras · Mathematics 2015-02-10 Farrukh Mukhamedov , Karimbergen Kudaybergenov

With the aim of applications to solving general integral equations, we introduce and study in this paper a special class of bi-Carleman kernels on $\mathbb{R}\times\mathbb{R}$, called $K^\infty$ kernels of Mercer type, whose property of…

Spectral Theory · Mathematics 2012-10-04 Igor M. Novitskii

In this paper we deal with a scale of reproducing kernel Hilbert spaces $H^{(n)}_2$, $n\ge 0$, which are linear subspaces of the classical Hilbertian Hardy space on the right-hand half-plane $\mathbb{C}^+$. They are obtained as ranges of…

Functional Analysis · Mathematics 2024-01-30 José E. Galé , Valentin Matache , Pedro J. Miana , Luis Sánchez--Lajusticia

In this paper we introduce a reproducing kernel Hilbert space defined on $\mathbb{R}^{d+1}$ as the tensor product of a reproducing kernel defined on the unit sphere $\mathbb{S}^{d}$ in $\mathbb{R}^{d+1}$ and a reproducing kernel defined on…

Numerical Analysis · Mathematics 2015-12-24 Johann S. Brauchart , Josef Dick , Lou Fang
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