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In this paper we prove Nikolskii's inequality on general compact Lie groups and on compact homogeneous spaces with the constant interpreted in terms of the eigenvalue counting function of the Laplacian on the space, giving the best constant…

Functional Analysis · Mathematics 2014-03-17 Erlan Nursultanov , Michael Ruzhansky , Sergey Tikhonov

In this article, we consider the random sampling in the image space $V$ of mixed Lebesgue space $L^{p,q}(\mathbb{R}^{n+1})$ under an idempotent integral operator. We assume some decay and regularity conditions of the kernel and approximate…

Functional Analysis · Mathematics 2022-11-08 Prashant Goyal , Dhiraj Patel , Sivananthan Sampath

Kernel interpolation is a fundamental technique for approximating functions from scattered data, with a well-understood convergence theory when interpolating elements of a reproducing kernel Hilbert space. Beyond this classical setting,…

Numerical Analysis · Mathematics 2025-05-19 Toni Karvonen , Gabriele Santin , Tizian Wenzel

Existing convergence of distributed optimization methods in non-Euclidean geometries typically rely on kernel assumptions: (i) global Lipschitz smoothness and (ii) bi-convexity of the associated Bregman divergence function. Unfortunately,…

Optimization and Control · Mathematics 2026-03-16 Junwen Qiu , Ziyang Zeng , Leilei Mei , Junyu Zhang

We study the density estimation problem with observations generated by certain dynamical systems that admit a unique underlying invariant Lebesgue density. Observations drawn from dynamical systems are not independent and moreover, usual…

Machine Learning · Statistics 2016-07-14 Hanyuan Hang , Ingo Steinwart , Yunlong Feng , Johan A. K. Suykens

We study quantitative stability results for different classes of Sobolev inequalities on general compact Riemannian manifolds. We prove that, up to constants depending on the manifold, a function that nearly saturates a critical Sobolev…

Analysis of PDEs · Mathematics 2024-05-28 Francesco Nobili , Davide Parise

This article studies sufficient conditions on families of approximating kernels which provide $N$--term approximation errors from an associated nonlinear approximation space which match the best known orders of $N$--term wavelet expansion.…

Functional Analysis · Mathematics 2019-03-15 Keaton Hamm , Jeff Ledford

In this work we address the problem of uniform approximation of differential forms starting from weak data defined by integration on rectifiable sets. We study approximation schemes defined by the projection operator L given by either…

Numerical Analysis · Mathematics 2025-12-02 Ludovico Bruni Bruno , Fwderico Piazzon

The approximation of probability measures on compact metric spaces and in particular on Riemannian manifoldsby atomic or empirical ones is a classical task in approximation and complexity theory with a wide range of applications. Instead of…

Optimization and Control · Mathematics 2021-01-12 Martin Ehler , Manuel Gräf , Sebastian Neumayer , Gabriele Steidl

We study uniform estimates for the family of fundamental Lagrange polynomials associated with any Leja sequence for the complex unit disk. The main result claims that all these polynomials are uniformly bounded on the disk, i.e.…

Complex Variables · Mathematics 2015-11-10 Amadeo Irigoyen

We develop an intrinsic, heat-kernel based fractional Sobolev framework on closed Riemannian manifolds and study the critical fractional Sobolev embedding. We determine the optimal coefficient of the lower-order $L^{p}$ term and prove that…

Analysis of PDEs · Mathematics 2025-12-23 Hao Tan , Zetian Yan , Zhipeng Yang

We develop a unified H\"older Lebesgue scale \(X^p\) and its weighted, higher order variants \(X^{k,p,a}\) to extend the Caffarelli Kohn Nirenberg (CKN) inequality beyond the classical Lebesgue regime. Within this framework we prove a two…

Analysis of PDEs · Mathematics 2025-10-02 Mengxia Dong

Interpolation and approximation of functionals with conditionally positive definite kernels is considered on sets of centers that are not determining for polynomials. It is shown that polynomial consistency is sufficient in order to define…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov

In this note we announce that under general hypotheses, wavelet-type expansions (of functions in $L^p,\ 1\leq p \leq \infty$, in one or more dimensions) converge pointwise almost everywhere, and identify the Lebesgue set of a function as a…

Functional Analysis · Mathematics 2016-09-06 Susan E. Kelly , Mark A. Kon , Louise A. Raphael

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 obtain an equivariant index theorem, or Lefschetz fixed-point formula, for isometries from complete Riemannian manifolds to themselves. The fixed-point set of such an isometry may be noncompact. We build on techniques developed by Roe.…

Differential Geometry · Mathematics 2024-01-10 Peter Hochs

Let L be an ample holomorphic line bundle over a compact complex Hermitian manifold X. Any fixed smooth Hermitian metric on L induces a Hilbert space structure on the space of global holomorphic sections with values in the k:th tensor power…

Complex Variables · Mathematics 2007-05-23 Robert Berman

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

The present paper is devoted to a theory of profile decomposition for bounded sequences in \emph{homogeneous} Sobolev spaces, and it enables us to analyze the lack of compactness of bounded sequences. For every bounded sequence in…

Functional Analysis · Mathematics 2022-02-15 Mizuho Okumura

Error estimates for kernel interpolation in Reproducing Kernel Hilbert Spaces (RKHS) usually assume quite restrictive properties on the shape of the domain, especially in the case of infinitely smooth kernels like the popular Gaussian…

Numerical Analysis · Mathematics 2025-01-09 Tizian Wenzel , Gabriele Santin , Bernard Haasdonk