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We introduce Besov spaces with variable smoothness and integrability by using the continuous version of Calder\`on reproducing formula. We show that our space is well-defined, i.e., independent of the choice of basis functions. We…

Functional Analysis · Mathematics 2017-11-27 Douadi Drihem

We investigate the stability of vector recovery from random linear measurements which have been either clipped or folded. This is motivated by applications where measurement devices detect inputs outside of their effective range. As…

Information Theory · Computer Science 2025-06-26 Pedro Abdalla , Daniel Freeman , João P. G. Ramos , Mitchell A. Taylor

We prove a sharp quantitative version of recent Faber-Krahn inequalities for the continuous Wavelet transforms associated to a certain family of Cauchy wavelet windows . Our results are uniform on the parameters of the family of Cauchy…

Functional Analysis · Mathematics 2024-11-26 Jaime Gómez , David Kalaj , Petar Melentijević , João P. G. Ramos

We prove sharp estimates for the Bergman projection in weighted Bergman spaces in terms of the Bekolle constant. Our main tools are a dyadic model dominating the operator and an adaptation of a method of Cruz-Uribe, Martell and Perez.

Classical Analysis and ODEs · Mathematics 2012-10-04 Sandra Pott , Maria Carmen Reguera

Herein, the theory of Bergman kernel is developed to the weighted case. A general form of weighted Bergman reproducing kernel is obtained, by which we can calculate concrete Bergman kernel functions for specific weights and domains.

Complex Variables · Mathematics 2020-09-08 Guan-Tie Deng , Yun Huang , Tao Qian

We prove that smooth $C^\infty$ functions are dense in weighted fractional Sobolev spaces on an arbitrary open set, under some mild conditions on the weight. We also obtain a~similar result in non-weighted spaces defined by some kernel…

Analysis of PDEs · Mathematics 2020-12-22 Bartłomiej Dyda , Michał Kijaczko

In this paper, we characterize the convexity of the Berezin range for finite-rank operators acting on the weighted Hardy space $\mathcal{H}_\gamma (\mathbb{D})$ over the unit disc $\mathbb{D}$. We provide a complete classification in terms…

Functional Analysis · Mathematics 2025-06-02 Sandip Kumar Maiti , Satyajit Sahoo , Gorachand Chakraborty

In this paper, we extend the correspondence between Bayesian estimation and optimal smoothing in a Reproducing Kernel Hilbert Space (RKHS) adding a convexe constraints on the solution. Through a sequence of approximating Hilbertian spaces…

Numerical Analysis · Mathematics 2021-07-13 X Bay , Laurence Grammont

We prove the sharp quantitative stability for a wide class of weighted isoperimetric inequalities. More precisely, we consider isoperimetric inequalities in convex cones with homogeneous weights. Inspired by the proof of such isoperimetric…

Analysis of PDEs · Mathematics 2020-06-25 Eleonora Cinti , Federico Glaudo , Aldo Pratelli , Xavier Ros-Oton , Joaquim Serra

In this paper, we present a unified approach to function approximation in reproducing kernel Hilbert spaces (RKHS) that establishes a previously unrecognized optimality property for several well-known function approximation techniques, such…

Statistics Theory · Mathematics 2013-01-08 Richard J. Barton

We prove that maximal operators of convolution type associated to smooth kernels are bounded in the homogeneous Hardy-Sobolev spaces $\dot{H}^{1,p}(\mathbb{R}^d)$ when $1/p < 1+1/d$. This range of exponents is sharp. As a by-product of the…

Classical Analysis and ODEs · Mathematics 2021-02-23 Carlos Pérez , Tiago Picon , Olli Saari , Mateus Sousa

The embedding constants of the Sobolev spaces $\mathring{W}^n_2[0;1] \hookrightarrow \mathring{W}^k_\infty[0; 1]$ ($0\leqslant k \leqslant n-1$) are studied. A relation of the embedding constants with the norms of the functionals $f\mapsto…

Functional Analysis · Mathematics 2020-01-03 Igor Sheipak , Tatiana Garmanova

In this paper we show that the weighted Bernstein-Walsh inequality in logarithmic potential theory is sharp up to some new universal constant, provided that the external field is given by a logarithmic potential. Our main tool for such…

Numerical Analysis · Mathematics 2017-07-26 Bernhard Beckermann , Thomas Helart

Regularized empirical risk minimization using kernels and their corresponding reproducing kernel Hilbert spaces (RKHSs) plays an important role in machine learning. However, the actually used kernel often depends on one or on a few…

Machine Learning · Statistics 2017-09-25 Andreas Christmann , Daohong Xiang , Ding-Xuan Zhou

We study kernel quadrature rules with convex weights. Our approach combines the spectral properties of the kernel with recombination results about point measures. This results in effective algorithms that construct convex quadrature rules…

Numerical Analysis · Mathematics 2022-10-12 Satoshi Hayakawa , Harald Oberhauser , Terry Lyons

This paper develops a frequentist solution to the functional calibration problem, where the value of a calibration parameter in a computer model is allowed to vary with the value of control variables in the physical system. The need of…

Methodology · Statistics 2021-07-20 Rui Tuo , Shiyuan He , Arash Pourhabib , Yu Ding , Jianhua Z. Huang

In this paper we present a comprehensive treatment of function spaces with logarithmic smoothness (Besov, Sobolev, Triebel-Lizorkin). We establish the following results: Sharp embeddings between the Besov spaces defined by differences and…

Functional Analysis · Mathematics 2018-12-27 Oscar Domínguez , Sergey Tikhonov

In this paper, we obtain the reversed Hardy-Littlewood-Sobolev inequality with vertical weights on the upper half space and discuss the extremal functions. We show that the sharp constants in this inequality are attained by introducing a…

Analysis of PDEs · Mathematics 2023-11-08 Jingbo Dou , Yunyun Hu , Jingjing Ma

We solved the problem of the best rational approximation of the Bergman kernels on the unit circle of the complex plane in the quadratic and uniform metrics.

Complex Variables · Mathematics 2017-11-16 Stanislav Chaichenko

The Patterson-Sullivan construction is proved almost surely to recover a Bergman function from its values on a random discrete subset sampled with the determinantal point process induced by the Bergman kernel on the unit ball $\mathbb{D}_d$…

Complex Variables · Mathematics 2021-01-26 Alexander I. Bufetov , Yanqi Qiu