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Related papers: On best constants in $L^2$ approximation

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Due to their flexibility, frames of Hilbert spaces are attractive alternatives to bases in approximation schemes for problems where identifying a basis is not straightforward or even feasible. Computing a best approximation using frames,…

Numerical Analysis · Mathematics 2020-07-08 Ben Adcock , Mohsen Seifi

Consider the integer best approximations of a linear form in $n\ge 2$ real variables. While it is well-known that any tail of this sequence always spans a lattice is sharp for any $n\ge 2$. In this paper, we determine the exact Hausdorff…

Number Theory · Mathematics 2025-09-17 Johannes Schleischitz

The upper estimates for the optimal constants of the multilinear Bohnenblust--Hille inequality obtained in [J. Funct. Anal. 264 (2013), 429--463] are here improved to: {0.1cm} {enumerate} For real scalars:…

Functional Analysis · Mathematics 2013-02-05 D. Nunez-Alarcon , D. Pellegrino , J. B. Seoane-Sepulveda , D. M. Serrano-Rodriguez

We study expansion/contraction properties of some common classes of mappings of the Euclidean space ${\mathbb R}^n, n\ge 2\,,$ with respect to the distance ratio metric. The first main case is the behavior of M\"obius transformations of the…

Complex Variables · Mathematics 2013-07-11 Slavko Simić , Matti Vuorinen , Gendi Wang

We establish upper bounds for the size of two-distance sets in Euclidean space and spherical two-distance sets. The main recipe for obtaining upper bounds is the spectral method. We construct Seidel matrices to encode the distance relations…

Combinatorics · Mathematics 2025-09-03 Wei-Chun Chen , Wei-Hsuan Yu

The aim of this paper is to obtain quantitative bounds for solutions to the optimal matching problem in dimension two. These bounds show that up to a logarithmically divergent shift, the optimal transport maps are close to be the identity…

Analysis of PDEs · Mathematics 2018-08-29 Michael Goldman , Martin Huesmann , Felix Otto

This paper investigates two inexact Levenberg-Marquardt (LM) methods for solving systems of nonlinear equations. Both approaches compute approximate search directions by solving the LM linear system inexactly, subject to specific…

Optimization and Control · Mathematics 2025-07-23 Bas Symoens , Morteza Rahimi , Masoud Ahookhosh

We give a comprehensive theoretical characterization of a nonparametric estimator for the $L_2^2$ divergence between two continuous distributions. We first bound the rate of convergence of our estimator, showing that it is…

Machine Learning · Statistics 2014-10-31 Akshay Krishnamurthy , Kirthevasan Kandasamy , Barnabas Poczos , Larry Wasserman

Consider the problem of finding a point in a unit $n$-dimensional $\ell_p$-ball ($p\ge 2$) such that the minimum of the weighted Euclidean distance from given $m$ points is maximized. We show in this paper that the recent…

Optimization and Control · Mathematics 2016-06-22 Zuping Wu , Yong Xia , Shu Wang

We are concerned with the optimal constants: in the Korn inequality under tangential boundary conditions on bounded sets $\Omega \subset \mathbb{R}^n$, and in the geometric rigidity estimate on the whole $\mathbb{R}^2$. We prove that the…

Analysis of PDEs · Mathematics 2015-01-09 Marta Lewicka , Stefan Muller

The Lipschitz constant is an important quantity that arises in analysing the convergence of gradient-based optimization methods. It is generally unclear how to estimate the Lipschitz constant of a complex model. Thus, this paper studies an…

Machine Learning · Statistics 2023-02-10 Calypso Herrera , Florian Krach , Josef Teichmann

In this paper we show that, with respect to the $L^2$ norm, three classes of functions in $H^r(0,1)$, defined by certain boundary conditions, admit optimal spline spaces of all degrees $\geq r-1$, and all these spline spaces have uniform…

Numerical Analysis · Mathematics 2019-07-09 Michael S. Floater , Espen Sande

A method for computing lower bounds on capacities of 2-dimensional constraints having a symmetric presentation in either the horizontal or the vertical direction is presented. The method is a generalization of the method of Calkin and Wilf…

Information Theory · Computer Science 2009-03-11 Erez Louidor , Brian Marcus

Monte Carlo approximations for random linear elliptic PDE constrained optimization problems are studied. We use empirical process theory to obtain best possible mean convergence rates $O(n^{-\frac{1}{2}})$ for optimal values and solutions,…

Optimization and Control · Mathematics 2021-06-14 Werner Römisch , Thomas M. Surowiec

Extending the methods developed in the author's previous paper and using adapted coordinate systems in two variables, an L^p boundedness theorem is proven for maximal operators over hypersurfaces in R^3 when p > 2. When the best possible p…

Classical Analysis and ODEs · Mathematics 2010-08-25 Michael Greenblatt

In dimensions $n\ge 2$ we obtain $L^{p_1}(\mathbb R^n) \times\dots\times L^{p_m}(\mathbb R^n)$ to $L^p(\mathbb R^n)$ boundedness for the multilinear spherical maximal function in the largest possible open set of indices and we provide…

Classical Analysis and ODEs · Mathematics 2019-11-12 Georgios Dosidis

Upper and lower bounds are given for the maximum Euclidean curvature among faces in Bianchi's fundamental polyhedron for $PSL_2(O)$ in the upper-half space model of hyperbolic space, where $O$ is an imaginary quadratic ring of integers with…

Number Theory · Mathematics 2022-05-31 Daniel E. Martin

We study the best uniform approximation by polynomials of fixed degree of the function sgn(x) on the union of two intervals symmetric with respect to the origin. We obtain precise asymptotics, with explicit constants, for the error of the…

Classical Analysis and ODEs · Mathematics 2008-08-08 Alexandre Eremenko , Peter Yuditskii

In this paper we investigate the existence of $L^{2}(\pi)$-spectral gaps for $\pi$-irreducible, positive recurrent Markov chains on general state space. We obtain necessary and sufficient conditions for the existence of…

Probability · Mathematics 2009-08-07 Achim Wuebker

We study pathwise approximation of scalar stochastic differential equations at a single time point or globally in time by means of methods that are based on finitely many observations of the driving Brownian motion. We prove lower error…

Numerical Analysis · Mathematics 2017-10-25 Mario Hefter , André Herzwurm , Thomas Müller-Gronbach
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