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This paper studies smoothing properties of the local fractional maximal operator, which is defined in a proper subdomain of the Euclidean space. We prove new pointwise estimates for the weak gradient of the maximal function, which imply…

Functional Analysis · Mathematics 2015-06-17 Toni Heikkinen , Juha Kinnunen , Janne Korvenpää , Heli Tuominen

Over a bounded strictly convex domain in $\mathbb{R}^n$ with smooth boundary, we establish a priori gradient estimate for an anisotropic mean curvature flow with prescribed contact angle and Neumann boundary conditions. The estimates…

Analysis of PDEs · Mathematics 2025-10-28 Can Cui , Nung Kwan Yip

We introduce a new method to prove lower estimates for the approximation error of general linear operators with smooth range in terms of classical moduli of smoothness and related $K$-functionals. In addition, we explicitly show how to…

Classical Analysis and ODEs · Mathematics 2017-06-05 Johannes Nagler

We obtain a priori estimates for solutions to the prescribed scalar curvature equation on $S^3$. The usual non-degeneracy assumption on the curvature function is replaced by a new condition, which is necessary and sufficient for the…

Analysis of PDEs · Mathematics 2007-05-23 Matthias Schneider

We introduce the Hardy spaces for Fourier integral operators on Riemannian manifolds with bounded geometry. We then use these spaces to obtain improved local smoothing estimates for Fourier integral operators satisfying the cinematic…

Analysis of PDEs · Mathematics 2024-01-31 Naijia Liu , Jan Rozendaal , Liang Song , Lixin Yan

This paper shows how abstract resolvent estimates imply local smoothing for solutions to the Schr\"odinger equation. If the resolvent estimate has a loss when compared to the optimal, non-trapping estimate, there is a corresponding loss in…

Analysis of PDEs · Mathematics 2007-11-19 Hans Christianson

In this short note, we prove a refinement of bilinear local smoothing estimate to Airy solutions, when the frequency support of two wave are separated. As an application we prove a smoothing property of a bilinear form.

Analysis of PDEs · Mathematics 2011-08-03 Soonsik Kwon , Tristan Roy

We discuss local linear smooth backfitting for additive non-parametric models. This procedure is well known for achieving optimal convergence rates under appropriate smoothness conditions. In particular, it allows for the estimation of each…

Statistics Theory · Mathematics 2022-01-27 Munir Hiabu , Enno Mammen , Joseph T. Meyer

The paper considers functional linear regression, where scalar responses $Y_1,...,Y_n$ are modeled in dependence of random functions $X_1,...,X_n$. We propose a smoothing splines estimator for the functional slope parameter based on a…

Statistics Theory · Mathematics 2009-02-26 Christophe Crambes , Alois Kneip , Pascal Sarda

We explore the connection between $k$-broad Fourier restriction estimates and sharp regularity $L^p-L^q$ local smoothing estimates for the solutions of the wave equation in $\mathbb{R}^{n}\times \mathbb{R}$ for all $n \geq 3$ via a…

Analysis of PDEs · Mathematics 2022-10-31 David Beltran , Olli Saari

We develop a wavelet like representation of functions in $L^p(\mathbb{R})$ based on their Fourier--Hermite coefficients; i.e., we describe an expansion of such functions where the local behavior of the terms characterize completely the…

Classical Analysis and ODEs · Mathematics 2016-08-08 H. N. Mhaskar

We show that a closed piecewise-linear hypersurface immersed in $R^n$ ($n\ge 3$) is the boundary of a convex body if and only if every point in the interior of each $(n-3)$-face has a neighborhood that lies on the boundary of some convex…

Computational Geometry · Computer Science 2007-05-23 Konstantin Rybnikov

This paper considers decentralized optimization of convex functions with mixed affine equality constraints involving both local and global variables. Constraints on global variables may vary across different nodes in the network, while…

Optimization and Control · Mathematics 2026-02-05 Demyan Yarmoshik , Nhat Trung Nguyen , Alexander Rogozin , Alexander Gasnikov

We consider nonparametric regression with functional covariates, that is, they are elements of an infinite-dimensional Hilbert space. A locally polynomial estimator is constructed, where an orthonormal basis and various tuning parameters…

Statistics Theory · Mathematics 2025-04-09 Moritz Jirak , Alois Kneip , Alexander Meister , Mario Pahl

We study a variant of the mean curvature flow for closed, convex hypersurfaces where the normal velocity is a nonhomogeneous function of the principal curvatures. We show that if the initial hypersurface satisfies a certain pinching…

Analysis of PDEs · Mathematics 2020-01-09 Tim Espin

In this article some explicit estimates on the decay of the convolutive inverse of a sequence are proved. They are derived from the functional calculus for Sobolev algebras. Applications include localization in spline-type spaces and…

Classical Analysis and ODEs · Mathematics 2008-04-25 José Luis Romero

This paper studies the problem of perturbed convex and smooth optimization. The main results describe how the solution and the value of the problem change if the objective function is perturbed. Examples include linear, quadratic, and…

Optimization and Control · Mathematics 2025-06-08 Vladimir Spokoiny

We develop a method for proving sup-norm and H\"older estimates for $\overline{\partial}$ on wide class of finite type pseudoconvex domains in $\mathbb{C}^n$. A fundamental obstruction to proving sup-norm estimates is the possibility of…

Complex Variables · Mathematics 2020-12-10 Dusty Grundmeier , Lars Simon , Berit Stensønes

We address in this paper the study of a geometric evolution, corresponding to a curvature which is non-local and singular at the origin. The curvature represents the first variation of the energy recently proposed as a variant of the…

Analysis of PDEs · Mathematics 2012-01-26 Antonin Chambolle , Massimiliano Morini , Marcello Ponsiglione

We develop new adaptive algorithms for variational inequalities with monotone operators, which capture many problems of interest, notably convex optimization and convex-concave saddle point problems. Our algorithms automatically adapt to…

Machine Learning · Computer Science 2021-08-30 Alina Ene , Huy L. Nguyen
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