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The variation of Hodge structure of a Calabi-Yau 3-fold induces a canonical K\"ahler metric on its Kuranishi moduli space, known as the Weil-Petersson metric. Similarly, special pseudo K\"ahler manifolds correspond to certain (abstract)…

dg-ga · Mathematics 2007-05-23 D. V. Alekseevsky , V. Cortes

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

This paper constructs unique compactly supported functions in Sobolev spaces that have minimal norm, maximal support, and maximal central value, under certain renormalizations. They may serve as optimized basis functions in interpolation or…

Numerical Analysis · Mathematics 2024-09-04 Robert Schaback

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

We show that there are well separated families of quantum expanders with asymptotically the maximal cardinality allowed by a known upper bound. This has applications to the "growth" of certain operator spaces: It implies asymptotically…

Operator Algebras · Mathematics 2014-12-23 Gilles Pisier

In this paper, we introduce homogeneous mixed Herz-Morrey spaces $M\dot{K}_{p,\vec{q}}^{\alpha,\lambda}(\mathbb{R}^n)$ and show it's some properties. Firstly, the boundedness of sublinear operators, fractional type operators in homogeneous…

Functional Analysis · Mathematics 2022-07-05 Mingwei Shi , Jiang Zhou

Random feature approximation is arguably one of the most popular techniques to speed up kernel methods in large scale algorithms and provides a theoretical approach to the analysis of deep neural networks. We analyze generalization…

Machine Learning · Computer Science 2023-08-30 Mike Nguyen , Nicole Mücke

We study the two-weighted off-diagonal compactness of commutators of rough singular integral operators $T_\Omega$ that are associated with a kernel $\Omega\in L^q(\mathbb{S}^{d-1})$. We establish a characterisation of compactness of the…

Classical Analysis and ODEs · Mathematics 2025-03-17 Aapo Laukkarinen , Jaakko Sinko

This note finds a new characterization of complete Nevanlinna-Pick kernels on the Euclidean unit ball. The classical theory of Sz.-Nagy and Foias about the characteristic function is extended in this note to a commuting tuple $\bfT$ of…

Functional Analysis · Mathematics 2023-05-01 Tirthankar Bhattacharyya , Abhay Jindal

Noncommutative K\"ahler structures were recently introduced as an algebraic framework for studying noncommutative complex geometry on quantum homogeneous spaces. In this paper, we introduce the notion of a \emph{compact quantum homogeneous…

Quantum Algebra · Mathematics 2026-03-17 Biswarup Das , Réamonn Ó Buachalla , Petr Somberg

We propose a new point of view for regularizing deep neural networks by using the norm of a reproducing kernel Hilbert space (RKHS). Even though this norm cannot be computed, it admits upper and lower approximations leading to various…

Machine Learning · Statistics 2019-05-15 Alberto Bietti , Grégoire Mialon , Dexiong Chen , Julien Mairal

We develop a unified geometric framework for nonparametric estimation based on the notion of Twin Kernel Spaces, defined as orbits of a reproducing kernel under a group action. This structure induces a family of transported RKHS geometries…

Statistics Theory · Mathematics 2025-12-16 Jocelyn Nembé

We develop an approximation theory in Hilbert spaces that generalizes the classical theory of approximation by entire functions of exponential type. The results advance harmonic analysis on manifolds and graphs, thus facilitating data…

Functional Analysis · Mathematics 2014-03-07 Isaac Z. Pesenson , Meyer Z. Pesenson

We characterize when Peetre's K-functional decays to zero slowly and we use this characterization to demonstrate certain strict inclusions between real interpolation spaces.

Functional Analysis · Mathematics 2019-10-10 J. M. Almira , P. Fernández-Martínez

Cubature formulas and geometrical designs are described in terms of reproducing kernels for Hilbert spaces of functions on the one hand, and Markov operators associated to orthogonal group representations on the other hand. In this way,…

Combinatorics · Mathematics 2007-05-23 Pierre De La Harpe , Claude Pache

In this article, the reproducing kernel Hilbert space [0, 1] is employed for solving a class of third-order periodic boundary value problem by using fitted reproducing kernel algorithm. The reproducing kernel function is built to get fast…

Numerical Analysis · Mathematics 2017-04-18 Asad Freihat , Radwan Abu-Gdairi , Hammad Khalil , Eman Abuteen , Mohammed Al-Smadi , Rahmat Ali Khan

We propose a novel adaptive learning algorithm based on iterative orthogonal projections in the Cartesian product of multiple reproducing kernel Hilbert spaces (RKHSs). The task is estimating/tracking nonlinear functions which are supposed…

Machine Learning · Computer Science 2015-10-28 Masahiro Yukawa

Given a fixed sigma-finite measure space $\left(X,\mathscr{B},\nu\right)$, we shall study an associated family of positive definite kernels $K$. Their factorizations will be studied with view to their role as covariance kernels of a variety…

Spectral Theory · Mathematics 2018-10-31 Palle Jorgensen , Feng Tian

These lecture notes endeavour to collect in one place the mathematical background required to understand the properties of kernels in general and the Random Fourier Features approximation of Rahimi and Recht (NIPS 2007) in particular. We…

Machine Learning · Computer Science 2020-05-05 Amitabha Bagchi

The purpose of the article is to generalize the concept of approximate Birkhoff-James orthogonality, in the semi-Hilbertian structure. Given a positive operator $ A $ on a Hilbert space $ \mathbb{H}, $ we define $ (\epsilon,A)- $approximate…

Functional Analysis · Mathematics 2024-08-14 Jeet Sen , Debmalya Sain , Kallol Paul