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Related papers: Off-spectral analysis of Bergman kernels

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This article develops a unified framework to study the asymptotic properties of all periodic spline-based estimators, that is, of regression, penalized and smoothing splines. The explicit form of the periodic Demmler-Reinsch basis in terms…

Statistics Theory · Mathematics 2016-02-23 Katsiaryna Schwarz , Tatyana Krivobokova

We obtain new explicit formulas for the Bergman kernel function on two families of Hartogs domains. To do so, we first compute the Bergman kernels on the slices of these Hartogs domains with some coordinates fixed, evaluate these kernel…

Complex Variables · Mathematics 2015-12-03 Zhenghui Huo

This is the second of two papers which address the problem of measuring the unredshifted power spectrum of fluctuations from a galaxy survey in optimal fashion. A key quantity is the Fisher matrix, which is the inverse of the covariance…

Astrophysics · Physics 2015-06-24 A. J. S. Hamilton

This paper studies Fefferman's program \cite{F3} of expressing the singularity of the Bergman kernel, for smoothly bounded strictly pseudoconvex domains $\Omega\subset\C^n$, in terms of local biholomorphic invariants of the boundary. By…

Complex Variables · Mathematics 2007-05-23 Kengo Hirachi

We study reproducing kernels of weighted spaces of polyanalytic polynomials on the complex plane. The results include a universality result concerning local blow-ups of the kernels near so called bulk points as well as an off-diagonal decay…

Complex Variables · Mathematics 2013-07-04 Antti Haimi

Understanding the spectral properties of kernels offers a principled perspective on generalization and representation quality. While deep models achieve state-of-the-art accuracy in molecular property prediction, kernel methods remain…

Machine Learning · Computer Science 2025-10-17 Asma Jamali , Tin Sum Cheng , Rodrigo A. Vargas-Hernández

We consider the kernel of a hypoelliptic diffusion beyond the case of sub-ellipticity or polynomial coefficients. We get a full asymptotic expansion for small times, based on a Duhamel-type comparison with an approximate polynomial kernel.…

Analysis of PDEs · Mathematics 2023-01-18 Pierre Perruchaud

In this paper, we establish the asymptotic expansion at infinity of gradient graph in dimension 2 with vanishing mean curvature at infinity. This corresponds to our previous results in higher dimensions and generalizes the results for…

Analysis of PDEs · Mathematics 2022-02-14 Zixiao Liu , Jiguang Bao

In this paper asymptotic equalities are found for the least upper bounds of deviations in the uniform metric of de la Vallee Poussin sums on classes of 2\pi-periodic (\psi,\beta)-differentiable functions admitting an analytic continuation…

Classical Analysis and ODEs · Mathematics 2012-08-31 A. S. Serdyuk , Ie. Yu. Ovsii , A. P. Musienko

This paper deals with the asymptotic study of the so-called canard solutions, which arise in the study of real singularly perturbed ODEs. Starting near an attracting branch of the "slow curve", those solutions are crossing a turning point…

Dynamical Systems · Mathematics 2008-12-12 Thomas Forget

This paper presents uniform convergence rates for kernel regression estimators, in the setting of a structural nonlinear cointegrating regression model. We generalise the existing literature in three ways. First, the domain to which these…

Statistics Theory · Mathematics 2015-05-08 James A. Duffy

The generalization performance of kernel ridge regression (KRR) exhibits a multi-phased pattern that crucially depends on the scaling relationship between the sample size $n$ and the underlying dimension $d$. This phenomenon is due to the…

Machine Learning · Computer Science 2022-05-16 Hong Hu , Yue M. Lu

We study spectrum of finite truncations of unbounded Jacobi matrices with periodically modulated entries. In particular, we show that under some hypotheses a sequence of properly normalized eigenvalue counting measures converge vaguely to…

Spectral Theory · Mathematics 2026-02-06 Grzegorz Świderski , Bartosz Trojan

Generalization beyond a training dataset is a main goal of machine learning, but theoretical understanding of generalization remains an open problem for many models. The need for a new theory is exacerbated by recent observations in deep…

Machine Learning · Statistics 2022-02-08 Abdulkadir Canatar , Blake Bordelon , Cengiz Pehlevan

We show how the essential spectral radius of a bounded positive kernel, acting on bounded functions, is linked to its lower approximation by certain absolutely continuous kernels. The standart Doeblin's condition can be interpreted in this…

Probability · Mathematics 2007-05-23 Hubert Hennion

We develop a coordinate-free probabilistic framework for determinantal point processes associated with Bergman kernels on compact complex manifolds. The basic issue is that Bergman kernels are naturally line-bundle-valued:…

Complex Variables · Mathematics 2026-05-27 Thibaut Lemoine

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 establish uniform (with respect to $x$, $y$) semiclassical asymptotics and estimates for the Schwartz kernel $e_h(x,y;\tau)$ of spectral projector for a second order elliptic operator inside domain under microhyperbolicity (but not…

Analysis of PDEs · Mathematics 2022-08-23 Victor Ivrii

Let $\phi\in C^\infty(\Complex^n)$ be a given real valued function. We assume that $\pr\ddbar\phi$ is non-degenerate of constant signature $(n_-,n_+)$ on $\Complex^n$. When $q=n_-$, it is well-known that the Bergman kernel for $(0,q)$ forms…

Complex Variables · Mathematics 2012-10-24 Chin-Yu Hsiao

We consider the Helmholtz equation in an angular sector partially covered by a homogeneous layer of small thickness, denoted $\varepsilon$. We propose in this work an asymptotic expansion of the solution with respect to $\varepsilon$ at any…

Analysis of PDEs · Mathematics 2026-02-17 Cédric Baudet
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