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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 show that if a reproducing kernel Hilbert space $H_K,$ consisting of functions defined on ${\bf E},$ enjoys Double Boundary Vanishing Condition (DBVC) and Linear Independent Condition (LIC), then for any preset natural number $n,$ and…

Complex Variables · Mathematics 2020-08-04 Wei Qu , Tao Qian , Guan-Tie Deng

Kernel methods form a powerful, versatile, and theoretically-grounded unifying framework to solve nonlinear problems in signal processing and machine learning. The standard approach relies on the kernel trick to perform pairwise evaluations…

Machine Learning · Computer Science 2019-12-11 Kan Li , Jose C. Principe

We introduce the notion of characteristic functions for commuting tuples of hypercontractions on Hilbert spaces, as a generalization of the notion of Sz.-Nagy and Foias characteristic functions of contractions. We present an explicit method…

Functional Analysis · Mathematics 2019-05-22 Monojit Bhattacharjee , B. Krishna Das , Jaydeb Sarkar

We provide a short argument to establish a Beurling-Lax-Halmos theorem for reproducing kernel Hilbert spaces whose kernel has a complete Nevanlinna-Pick factor. We also record factorization results for pairs of nested invariant subspaces.

Functional Analysis · Mathematics 2020-09-23 Raphaël Clouâtre , Michael Hartz , Dominik Schillo

We characterize the de Branges-Rovnyak spaces with complete Nevanlinna-Pick property. Our method relies on the general theory of reproducing kernel Hilbert spaces.

Functional Analysis · Mathematics 2020-03-12 Cheng Chu

The paper presents a new functional model for completely non-unitary contractions on a Hilbert space. This model is based on the observation that the theory of contractions shares a common geometric basis with the extension theory of…

Functional Analysis · Mathematics 2025-03-19 Wang Yicao

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

Pick spaces are a class of reproducing kernel Hilbert spaces that generalize the classical Hardy space and the Drury--Arveson reproducing kernel spaces. We give characterizations of certain contractively included subspaces of Pick spaces.…

Functional Analysis · Mathematics 2013-05-30 Chafiq Benhida , Dan Timotin

We present an exact, closed-form expression for the Newtonian potential of the characteristic function associated with two overlapping discs in the plane. This setting naturally arises when discretising nonlocal interaction terms present in…

Analysis of PDEs · Mathematics 2025-12-22 Andrés Miniguano-Trujillo

In this paper, we give several characterizations of Herglotz-Nevanlinna functions in terms of a specific type of positive semi-definite functions called Poisson-type functions. This allows us to propose a multidimensional analogue of the…

Complex Variables · Mathematics 2022-01-05 Mitja Nedic

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

We connect shift-invariant characteristic kernels to infinitely divisible distributions on $\mathbb{R}^{d}$. Characteristic kernels play an important role in machine learning applications with their kernel means to distinguish any two…

Machine Learning · Statistics 2016-10-26 Yu Nishiyama , Kenji Fukumizu

In this paper we propose a different (and equivalent) norm on $S^{2} ({\mathbb{D}})$ which consists of functions whose derivatives are in the Hardy space of unit disk. The reproducing kernel of $S^{2}({\mathbb{D}})$ in this norm admits an…

Functional Analysis · Mathematics 2018-08-31 Caixing Gu , Shuaibing Luo

Given a domain $\Omega$ in $\mathbb{C}^m$, and a finite set of points $z_1,z_2,\ldots, z_n\in \Omega$ and $w_1,w_2,\ldots, w_n\in \mathbb{D}$ (the open unit disc in the complex plane), the \textit{Pick interpolation problem} asks when there…

Functional Analysis · Mathematics 2023-09-13 Tirthankar Bhattacharyya , Anindya Biswas , Vikramjeet Singh Chandel

The theory of positive kernels and associated reproducing kernel Hilbert spaces, especially in the setting of holomorphic functions, has been an important tool for the last several decades in a number of areas of complex analysis and…

Operator Algebras · Mathematics 2016-02-03 Joseph A. Ball , Gregory Marx , Victor Vinnikov

Let $(\mathcal{H}_k, \mathcal{H}_{\ell})$ be a pair of Hilbert function spaces with kernels $k, \ell$. In a 2005 paper, Shimorin showed that a certain factorization condition on $(k, \ell)$ yields a commutant lifting theorem for multipliers…

Functional Analysis · Mathematics 2025-08-27 Scott McCullough , Georgios Tsikalas

We investigate isometric and algebraic isomorphism problems for multiplier algebras associated with Dirichlet series kernels that possess the complete Nevanlinna-Pick (CNP) property. A central aspect of our work is the explicit…

Functional Analysis · Mathematics 2026-05-15 Hamidul Ahmed , B. Krishna Das , Chaman Kumar Sahu

We characterize those generating functions k that produce weighted Hardy spaces of the unit disk D supporting nontrivial Hermitian weighted composition operators. Our characterization shows that the spaces associated with the "classical…

Functional Analysis · Mathematics 2011-04-08 Paul Bourdon , Wenling Shang

Positive-definite kernel functions are fundamental elements of kernel methods and Gaussian processes. A well-known construction of such functions comes from Bochner's characterization, which connects a positive-definite function with a…

Machine Learning · Statistics 2016-10-28 Jie Chen , Dehua Cheng , Yan Liu