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In this paper, we establish quantitative estimates for nonlinear sampling Kantorovich operators in terms of the modulus of continuity in the setting of Orlicz spaces. This general frame allows us to directly deduce some quantitative…

Functional Analysis · Mathematics 2021-02-18 Nursel Cetin , Danilo Costarelli , Gianluca Vinti

We prove a Lipschitz approximation with superlinear error terms for integral currents $\omega$-minimizing the area functional, where $\omega$ is a modulus of continuity satisfying a Dini condition. We also present an almost monotonicity…

Analysis of PDEs · Mathematics 2024-09-06 Reinaldo Resende

Let $L$ be a homogeneous divergence form higher order elliptic operator with complex bounded measurable coefficients on $\mathbb{R}^n$ and $X$ a ball quasi-Banach function space on $\mathbb{R}^n$ satisfying some mild assumptions. Denote by…

Functional Analysis · Mathematics 2022-07-11 Xiaosheng Lin , Dachun Yang , Sibei Yang , Wen Yuan

We investigate a class of composite nonconvex functions, where the outer function is the sum of univariate extended-real-valued convex functions and the inner function is the limit of difference-of-convex functions. A notable feature of…

Optimization and Control · Mathematics 2024-11-21 Hanyang Li , Ying Cui

In this paper, we considered the problem of the simultaneous approximation of a function and its derivatives by means of the well-known neural network (NN) operators activated by sigmoidal function. Other than a uniform convergence theorem…

Functional Analysis · Mathematics 2025-02-25 Marco Cantarini , Danilo Costarelli

We consider the fundamental learning problem of estimating properties of distributions over large domains. Using a novel piecewise-polynomial approximation technique, we derive the first unified methodology for constructing sample- and…

Machine Learning · Computer Science 2020-03-18 Yi Hao , Alon Orlitsky

Let $0 \leq \alpha<n$, $M_{\alpha}$ be the fractional maximal operator, $M^{\sharp}$ be the sharp maximal operator and $b$ be the locally integrable function. Denote by $[b, M_{\alpha}]$ and $[b, M^{\sharp}]$ be the commutators of the…

Functional Analysis · Mathematics 2024-07-08 Heng Yang , Jiang Zhou

We provide comparison principles for convex functions through its proximal mappings. Consequently, we prove that the norm of the proximal operator determines a convex the function up to a constant. A new characterization of Lipschitzianity…

Optimization and Control · Mathematics 2020-07-30 Emilio Vilches

We introduce function spaces for the treatment of non-linear parabolic equations with variable $\log$-H\"older continuous exponents, which only incorporate information of the symmetric part of a gradient. As an analogue of Korn's inequality…

Analysis of PDEs · Mathematics 2020-10-14 A. Kaltenbach , R. Růžička

In this paper, we analyze the behavior of various non-parametric local regression estimators, i.e. estimators that are based on local averaging, for estimating a Lipschitz regression function at a fixed point, or in sup-norm. We first prove…

Statistics Theory · Mathematics 2025-07-11 Jérémy Bettinger , François Portier , Adrien Saumard

We consider the composite minimization problem with the objective function being the sum of a continuously differentiable and a merely lower semicontinuous and extended-valued function. The proximal gradient method is probably the most…

Optimization and Control · Mathematics 2024-11-20 Christian Kanzow , Leo Lehmann

This work investigates a dynamical system functioning as a nonsmooth adaptation of the continuous Newton method, aimed at minimizing the sum of a primal lower-regular and a locally Lipschitz function, both potentially nonsmooth. The…

Optimization and Control · Mathematics 2024-12-10 Juan Guillermo Garrido , Pedro Pérez-Aros , Emilio Vilches

The goal of the paper is development of an optimization method with the superlinear convergence rate for a nonsmooth convex function. For optimization an approximation is used that is similar to the Steklov integral averaging. The…

Optimization and Control · Mathematics 2023-08-03 I. M. Prudnikov

The goal of this note is to prove that every real-valued Lipschitz function on a Banach space can be pointwise approximated on a given $\sigma$-compact set by smooth cylindrical functions whose asymptotic Lipschitz constants are controlled.…

Functional Analysis · Mathematics 2024-09-04 Enrico Pasqualetto

We start in this paper a systematic study of the superpositions of elliptic operators with different orders, mixing classical and fractional scenarios. For concreteness, we focus on the sum of the Laplacian and the fractional Laplacian, and…

Analysis of PDEs · Mathematics 2021-10-26 Stefano Biagi , Serena Dipierro , Enrico Valdinoci , Eugenio Vecchi

As is well known absolute convergence and unconditional convergence for series are equivalent only in finite dimensional Banach spaces. Replacing the classical notion of absolutely summing operators by the notion of 1 summing operators \[…

Functional Analysis · Mathematics 2016-09-06 Marius Junge

This article provides a power series summability based Korovkin type approximation theorem for any fuzzy sequence of positive linear operators. Using the notion of fuzzy modulus of smoothness, we also derive an associated approximation…

General Mathematics · Mathematics 2022-02-07 Behar Baxhaku , Purshottam Narain Agrawal , Rahul Shukla

This paper focuses on the metric properties of L\"uroth well approximable numbers, studying analogous of classical results, namely the Khintchine Theorem, the Jarn\'ik--Besicovitch Theorem, and the result of Dodson. A supplementary proof is…

Number Theory · Mathematics 2025-02-13 Ying Wai Lee

For an arbitrary self-adjoint operator $B$ in a Hilbert space $H$, we present direct and inverse theorems establishing the relationship between the degree of smoothness of a vector $x \in H$ with respect to the operator $B$, the rate of…

Functional Analysis · Mathematics 2007-09-27 S. M. Torba , M. L. Gorbachuk , Ya. I. Grushka

We present a new approach to convergence rate results for variational regularization. Avoiding Bregman distances and using image space approximation rates as source conditions we prove a nearly minimax theorem showing that the modulus of…

Numerical Analysis · Mathematics 2021-07-07 Philip Miller