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Much recent work has addressed the solution of a family of partial differential equations by computing the inverse operator map between the input and solution space. Toward this end, we incorporate function-valued reproducing kernel Hilbert…

Numerical Analysis · Mathematics 2022-04-05 Kaijun Bao , Xu Qian , Ziyuan Liu , Songhe Song

In this paper, we study random sampling on reproducing kernel space $V$, which is a range of an idempotent integral operator. Under certain decay condition on the integral kernel, we show that any element in $V$ can be approximated by an…

Functional Analysis · Mathematics 2022-09-16 Dhiraj Patel , Sivananthan Sampath

For $S$ a contractive analytic operator-valued function on the unit disk ${\mathbb D}$, de Branges and Rovnyak associate a Hilbert space of analytic functions ${\mathcal H}(S)$. A companion survey provides equivalent definitions and basic…

Classical Analysis and ODEs · Mathematics 2014-05-14 Joseph A. Ball , Vladimir Bolotnikov

In this paper, we study vector valued de Branges spaces associated with a de Branges operator, defined as a pair of Fredholm operator valued analytic functions on a domain symmetric with respect to the unit circle. Using a suitable direct…

Functional Analysis · Mathematics 2026-04-14 Bharti Garg , Santanu Sarkar

A general interpolation problem with operator argument is studied for functions f from the de Branges-Rovnyak space H(s) associated with an analytic function s mapping the open unit disk D into the closed unit disk. The interpolation…

Functional Analysis · Mathematics 2018-04-24 Joseph A. Ball , Vladimir Bolotnikov , Sanne Ter Horst

As we all known, there is still a long way for us to solve arbitrary multivariate Lagrange interpolation in theory. Nevertheless, it is well accepted that theories about Lagrange interpolation on special point sets should cast important…

Commutative Algebra · Mathematics 2010-03-17 Tian Dong , Xiaoying Wang , Shugong Zhang , Peng Li

We prove that homological filling functions over a ring $R$ equipped with the discrete norm are quasi-isometry invariants for all groups of type $\mathrm{FP}_n$. This confirms a conjecture of Bader-Kropholler-Vankov in the case of discrete…

Group Theory · Mathematics 2026-03-10 Jannis Weis

In the present paper, we introduce the notion of nearly holomorphic Drinfeld modular forms and study an analogue of Maass-Shimura operators in this context. Furthermore, for a given nearly holomorphic Drinfeld modular form, we show that its…

Number Theory · Mathematics 2023-09-06 Yen-Tsung Chen , Oğuz Gezmiş

We introduce a complex-valued counterpart of the representer theorem in machine learning. We study several learning and minimization problems in reproducing kernel Hilbert spaces (RKHSs), with the aim of identifying appropriate input-output…

Functional Analysis · Mathematics 2026-04-28 Natanael Alpay , Antonino De Martino , Kamal Diki

We investigate an interpolation/extrapolation method that, given scattered observations of the Fourier transform, approximates its inverse. The interpolation algorithm takes advantage of modelling the available data via a shape-driven…

Numerical Analysis · Mathematics 2021-09-22 Emma Perracchione , Anna Maria Massone , Michele Piana

Kalton and Mitrea characterized complex interpolation spaces of quasi-Banach function spaces as Calder\'on products if both interpolants are separable. We show that one separability assumption may be omitted and establish a…

Functional Analysis · Mathematics 2024-12-18 Moritz Egert , Benjamin W. Kosmala

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

Supervised learning in reproducing kernel Hilbert space (RKHS) and vector-valued RKHS (vvRKHS) has been investigated for more than 30 years. In this paper, we provide a new twist to this rich literature by generalizing supervised learning…

Machine Learning · Statistics 2024-06-27 Yuka Hashimoto , Masahiro Ikeda , Hachem Kadri

We study the approximation of a square-integrable function from a finite number of evaluations on a random set of nodes according to a well-chosen distribution. This is particularly relevant when the function is assumed to belong to a…

Machine Learning · Statistics 2024-11-13 Ayoub Belhadji , Rémi Bardenet , Pierre Chainais

This paper generalizes regularized regression problems in a hyper-reproducing kernel Hilbert space (hyper-RKHS), illustrates its utility for kernel learning and out-of-sample extensions, and proves asymptotic convergence results for the…

Machine Learning · Computer Science 2022-10-20 Fanghui Liu , Lei Shi , Xiaolin Huang , Jie Yang , Johan A. K. Suykens

The Carleman operator is defined as integral operator with kernel $(t+s)^{-1}$ in the space $L^2 ({\Bbb R}_{+}) $. This is the simplest example of a Hankel operator which can be explicitly diagonalized. Here we study a class of self-adjoint…

Functional Analysis · Mathematics 2014-04-29 D. R. Yafaev

This paper investigates a general regularization framework for unsupervised domain adaptation in vector-valued regression under the covariate shift assumption, utilizing vector-valued reproducing kernel Hilbert spaces (vRKHS). Covariate…

Statistics Theory · Mathematics 2026-01-30 Markus Holzleitner , Sergiy Pereverzyev , Sergei V. Pereverzyev , Vaibhav Silmana , S. Sivananthan

A new generalization of shifted thin plate splines $$\varphi(x)=(c^{2d}+||x||^{2d})\log\left(c^{2d}+||x||^{2d}\right),\qquad x\in\mathbb{R}^n, d\in \mathbb{N}, c>0$$ is presented to increase the accuracy of quasi-interpolation further. With…

Numerical Analysis · Mathematics 2024-06-25 Mathis Ortmann , Martin Buhmann

We study reproducing kernels, and associated reproducing kernel Hilbert spaces (RKHSs) $\mathscr{H}$ over infinite, discrete and countable sets $V$. In this setting we analyze in detail the distributions of the corresponding Dirac…

Functional Analysis · Mathematics 2015-01-13 Palle Jorgensen , Feng Tian

Recently, there has been growing interest in characterizing the function spaces underlying neural networks. While shallow and deep scalar-valued neural networks have been linked to scalar-valued reproducing kernel Banach spaces (RKBS),…

Functional Analysis · Mathematics 2025-10-02 Sven Dummer , Tjeerd Jan Heeringa , José A. Iglesias