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We make use of the Bergman kernel function to study quadrature domains for square-integrable holomorphic functions of several variables. Emphasis is given to generalizing biholomorphic mapping properties of planar quadrature domains to the…

Complex Variables · Mathematics 2016-10-25 Alan R. Legg

We develop a kernel-based approach for estimating the spatially varying Sobolev regularity~$s$ of an unknown $d$-variate function~$f$ from scattered sampling data, which quantifies the degree of local differentiability supported by the…

Numerical Analysis · Mathematics 2026-01-29 Xiaobin Li , Leevan Ling , Yizhong Sun

We study multivariable Christoffel-Darboux kernels, which may be viewed as reproducing kernels for antisymmetric orthogonal polynomials, and also as correlation functions for products of characteristic polynomials of random Hermitian…

Classical Analysis and ODEs · Mathematics 2008-04-24 Hjalmar Rosengren

Many supervised learning problems involve high-dimensional data such as images, text, or graphs. In order to make efficient use of data, it is often useful to leverage certain geometric priors in the problem at hand, such as invariance to…

Machine Learning · Statistics 2021-11-08 Alberto Bietti , Luca Venturi , Joan Bruna

Properties of local and global slope of a function and its approximate critical points sets are studied in relation to determination of the function.

Functional Analysis · Mathematics 2025-02-20 Milen Ivanov , Nadia Zlateva

The present work develops certain analytical tools required to construct and compute invariant kernels on the space of complex covariance matrices. The main result is the $\mathrm{L}^1$--Godement theorem, which states that any invariant…

Functional Analysis · Mathematics 2025-04-17 Salem Said , Franziskus Steinert , Cyrus Mostajeran

We show that kernel-based quadrature rules for computing integrals can be seen as a special case of random feature expansions for positive definite kernels, for a particular decomposition that always exists for such kernels. We provide a…

Machine Learning · Computer Science 2015-11-10 Francis Bach

Due to its connection to the diffeomorphism group, nonlinear quantum mechanics may play an important role in quantum geometry. The Doebner-Goldin nonlinearity (arising from representations of the diffeomorphism group) amplifies nonlocal…

Quantum Physics · Physics 2007-05-23 George Svetlichny

A mesh-free numerical method for solving linear elliptic PDE's using the local kernel theory that was developed for manifold learning is proposed. In particular, this novel approach exploits the local kernel theory which allows one to…

Numerical Analysis · Mathematics 2019-07-02 Faheem Gilani , John Harlim

In this paper we establish some general results on local behavior of holomorphic functions along complex submanifolds of $\Co^{N}$. As a corollary, we present multi-dimensional generalizations of an important result of Coman and Poletsky on…

Complex Variables · Mathematics 2009-11-13 Alexander Brudnyi

We develop a new mathematical approach to diffeomorphism invariant quantum states for the quantisation of general field theories such as general relativity and modified gravity. Treating quantum fields as fibre bundles, we discuss operators…

Mathematical Physics · Physics 2017-10-31 James Moffat , Teodora Oniga , Charles H. -T. Wang

The main goal of this paper is to study some local and global properties of secant varieties of algebraic curves. These results complement our previous work [8] by addressing issues given therein and providing solutions to problems raised…

Algebraic Geometry · Mathematics 2026-04-30 Lawrence Ein , Wenbo Niu , Jinhyung Park

Smoothing a signal based on local neighborhoods is a core operation in machine learning and geometry processing. On well-structured domains such as vector spaces and manifolds, the Laplace operator derived from differential geometry offers…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Nathan Kessler , Robin Magnet , Jean Feydy

Colombeau algebras constitute a convenient framework for performing nonlinear operations like multiplication on Schwartz distributions. Many variants and modifications of these algebras exist for various applications. We present a…

Functional Analysis · Mathematics 2013-07-02 E. A. Nigsch

Most state-of-the-art graph kernels only take local graph properties into account, i.e., the kernel is computed with regard to properties of the neighborhood of vertices or other small substructures. On the other hand, kernels that do take…

Machine Learning · Computer Science 2017-09-25 Christopher Morris , Kristian Kersting , Petra Mutzel

We study the algebra of complex polynomials which remain invariant under the action of the local Clifford group under conjugation. Within this algebra, we consider the linear spaces of homogeneous polynomials degree by degree and construct…

Quantum Physics · Physics 2009-11-10 Maarten Van den Nest , Jeroen Dehaene , Bart De Moor

The present paper deals with singular integrals with variable Caldero'n-Zygmund type kernels satisfying mixed homogeneity condition. The continuity of these operators in The Lebesgue spaces is well studied by Fabes and Rivie're. Our goal is…

Functional Analysis · Mathematics 2025-12-10 L. G. Softova

We give several unequivalent notions of convergency of meromorphic functions and more generally meromorphic mappings (strong, weak, $\Gamma $-convergency and some others). Relations between them are investigated. A version of Rouche theorem…

Complex Variables · Mathematics 2016-09-07 Sergei Ivashkovich

New integral kernels describing the full-wave dielectric response of Maxwellian tokamak plasmas are presented. They realistically account for the rotational transform and for wave dispersion in presence of equilibrium magnetic field…

Plasma Physics · Physics 2020-10-28 P. U. Lamalle

A fundamental drawback of kernel-based statistical models is their limited scalability to large data sets, which requires resorting to approximations. In this work, we focus on the popular Gaussian kernel and on techniques to linearize…

Machine Learning · Statistics 2022-04-13 Jonas Wacker , Maurizio Filippone
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