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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

We use a classical characterisation to prove that functions which are bounded away from zero cannot be elements of reproducing kernel Hilbert spaces whose reproducing kernels decays to zero in a suitable way. The result is used to study…

Functional Analysis · Mathematics 2021-02-23 Toni Karvonen

We study properties of the weighted Bergman hernel on the unit disk. As we restrict to the subspace of all functions that vanish at a given point, we obtain the reproducing kernel for the subspace from the above weighted Bergman kernel via…

Complex Variables · Mathematics 2007-05-23 Alexandru Aleman , Haakan Hedenmalm , Stefan Richter , Carl Sundberg

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 give a complete characterisation of the spaces $\dot{B}^{\alpha}_{p,q}$ and $\dot{F}^{\alpha}_{p,q}$ by using a non-smooth kernel satisfying near minimal conditions. The tools used include a Stromberg-Torchinsky type estimate for certain…

Functional Analysis · Mathematics 2016-06-29 Huy-Qui Bui , Timothy Candy

We consider a reproducing kernel Hilbert space of discrete entire functions on the square lattice $\mathbb Z^2$ inspired by the classical Paley-Wiener space of entire functions of exponential growth in the complex plane. For such space we…

Complex Variables · Mathematics 2025-07-15 Alessandro Monguzzi , Matteo Monti

Kernel matrices are crucial in many learning tasks such as support vector machines or kernel ridge regression. The kernel matrix is typically dense and large-scale. Depending on the dimension of the feature space even the computation of all…

Machine Learning · Computer Science 2023-12-04 Franziska Nestler , Martin Stoll , Theresa Wagner

Let $S$ be the shift operator on the Hardy space $H^2$ and let $S^*$ be its adjoint. A closed subspace $\FF$ of $H^2$ is said to be nearly $S^*$-invariant if every element $f\in\FF$ with $f(0)=0$ satisfies $S^*f\in\FF$. In particular, the…

Functional Analysis · Mathematics 2010-01-26 Chevrot Nicolas

We return to Takagi's variational principle, generalized after forty years to two complex variables by Pfister. Both isolating some extremal rational functions associated to a bounded holomorphic function in the unit disk, respectively the…

Complex Variables · Mathematics 2025-09-22 Mainak Bhowmik , Mihai Putinar

We investigate a recently proposed family of positive-definite kernels that mimic the computation in large neural networks. We examine the properties of these kernels using tools from differential geometry; specifically, we analyze the…

Machine Learning · Computer Science 2011-12-19 Youngmin Cho , Lawrence K. Saul

We introduce a Cherednik kernel and a hypergeometric function for integral root systems and prove their relation to spherical functions associated with Riemannian symmetric spaces of reductive Lie groups. Furthermore, we characterize the…

Classical Analysis and ODEs · Mathematics 2024-10-10 Dominik Brennecken

The full Fock space over $\mathbb C ^d$ can be identified with the free Hardy space, $H^2 (\mathbb B ^d _\mathbb N)$ - the unique non-commutative reproducing kernel Hilbert space corresponding to a non-commutative Szeg\"{o} kernel on the…

Operator Algebras · Mathematics 2019-06-19 Michael T. Jury , Robert T. W. Martin

The paper introduces new sufficient conditions of strict positive definiteness for kernels on d-dimensional spheres which are not radially symmetric but possess specific coefficient structures. The results use the series expansion of the…

Numerical Analysis · Mathematics 2021-05-07 Martin Buhmann , Janin Jäger

This survey is an introduction to positive definite kernels and the set of methods they have inspired in the machine learning literature, namely kernel methods. We first discuss some properties of positive definite kernels as well as…

Machine Learning · Statistics 2009-12-04 Marco Cuturi

For a collection of reproducing kernels k which includes those for the Hardy space of the polydisk and ball and for the Bergman space, k is a complete Pick kernel if and only if the multiplier algebra of the Hilbert space H^2(k) associated…

Functional Analysis · Mathematics 2011-11-18 Scott McCullough , Tavan T. Trent

We show that certain monotone functionals on the Hardy spaces and convex functionals on the Bergman spaces are maximized at the normalized reproducing kernels among the functions of norm $1$, thus proving the contractivity conjecture of…

Complex Variables · Mathematics 2022-03-24 Aleksei Kulikov

We show that properties of pairs of finite, positive and regular Borel measures on the complex unit circle such as domination, absolute continuity and singularity can be completely described in terms of containment and intersection of their…

Functional Analysis · Mathematics 2025-08-27 Jashan Bal , Robert T. W. Martin , Fouad Naderi

We consider positive semidefinite kernels valued in the $*$-algebra of continuous and continuously adjointable operators on a VH-space (Vector Hilbert space in the sense of Loynes) and that are invariant under actions of $*$-semigroups. For…

Operator Algebras · Mathematics 2025-11-04 Serdar Ay , Aurelian Gheondea

We study reproducing kernel Hilbert spaces introduced as ranges of generalized Ces\`aro-Hardy operators, in one real variable and in one complex variable. Such spaces can be seen as formed by absolutely continuous functions on the positive…

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

We study how iterated and composed completely positive maps act on operator-valued kernels. Each kernel is realized inside a single Hilbert space where composition corresponds to applying bounded creation operators to feature vectors. This…

Functional Analysis · Mathematics 2025-11-18 James Tian
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