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Many problems of theoretical and practical interest involve finding an optimum over a family of convex functions. For instance, finding the projection on the convex functions in $H^k(\Omega)$, and optimizing functionals arising from some…

Numerical Analysis · Mathematics 2008-04-11 Néstor E. Aguilera , Pedro Morin

We study the radius of absolute monotonicity R of rational functions with numerator and denominator of degree s that approximate the exponential function to order p. Such functions arise in the application of implicit s-stage, order p…

Numerical Analysis · Mathematics 2019-02-20 Lajos Loczi , David I. Ketcheson

This work studies optimal polynomial approximants (OPAs) in the classical Hardy spaces on the unit disk, $H^p$ ($1 < p < \infty$). For fixed $f\in H^p$ and $n\in\mathbb{N}$, the OPA of degree $n$ associated to $f$ is the polynomial which…

Functional Analysis · Mathematics 2024-04-24 Raymond Cheng , Christopher Felder

Let $\A$ be the operator which assigns to each $m \times n$ matrix-valued function on the unit circle with entries in $H^\infty + C$ its unique superoptimal approximant in the space of bounded analytic $m \times n$ matrix-valued functions…

Functional Analysis · Mathematics 2016-09-06 Vladimir V. Peller , Nicholas J. Young

We establish fractional Hardy inequality on bounded domains in $\mathbb{R}^{d}$ with inverse of distance function from smooth boundary of codimension $k$, where $k=2, \dots,d$, as weight function. The case $sp=k$ is the critical case, where…

Analysis of PDEs · Mathematics 2026-02-13 Adimurthi , Prosenjit Roy , Vivek Sahu

This paper studies best finitely supported approximations of one-dimensional probability measures with respect to the $L^r$-Kantorovich (or transport) distance, where either the locations or the weights of the approximations' atoms are…

Probability · Mathematics 2019-03-06 Chuang Xu , Arno Berger

We show that $C^0$-fine approximation of convex functions by smooth (or real analytic) convex functions on $\R^d$ is possible in general if and only if $d=1$. Nevertheless, for $d\geq 2$ we give a characterization of the class of convex…

Classical Analysis and ODEs · Mathematics 2012-01-24 Daniel Azagra

Symmetric submodular functions are an important family of submodular functions capturing many interesting cases including cut functions of graphs and hypergraphs. Maximization of such functions subject to various constraints receives little…

Data Structures and Algorithms · Computer Science 2016-04-19 Moran Feldman

In this article, by means of the matrix-weighted grand maximal function we first introduce the variable Hardy space $H^{p(\cdot)}_W$ on $\mathbb{R}^n$ with the $\mathscr{A}_{p(\cdot),\infty}$ matrix weight $W$ and with the variable exponent…

Functional Analysis · Mathematics 2026-05-26 Yiqun Chen , Dachun Yang , Wen Yuan , Zongze Zeng

We consider a robust variant of the classical $k$-median problem, introduced by Anthony et al. \cite{AnthonyGGN10}. In the \emph{Robust $k$-Median problem}, we are given an $n$-vertex metric space $(V,d)$ and $m$ client sets $\set{S_i…

Data Structures and Algorithms · Computer Science 2013-09-19 Sayan Bhattacharya , Parinya Chalermsook , Kurt Mehlhorn , Adrian Neumann

We study estimates for Hardy space norms of analytic projections. We first find a sufficient condition for the Bergman projection of a function in the unit disc to belong to the Hardy space $H^p$ for $1 < p < \infty$. We apply the result to…

Complex Variables · Mathematics 2019-09-24 Timothy Ferguson

We obtain the best approximation in $L^1(\R)$, by entire functions of exponential type, for a class of even functions that includes $e^{-\lambda|x|}$, where $\lambda >0$, $\log |x|$ and $|x|^{\alpha}$, where $-1 < \alpha < 1$. We also give…

Classical Analysis and ODEs · Mathematics 2011-06-06 Emanuel Carneiro , Jeffrey D. Vaaler

We study the approximation of measurable functions on the hypercube by functions arising from affine neural networks. Our main achievement is an approximation of any measurable function $f \colon W_n \to [-1,1]$ up to a prescribed precision…

Machine Learning · Computer Science 2019-01-30 Andreas Thom

Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite-dimensional functions from limited samples. This is a key task in computational science and engineering, e.g., surrogate modelling in…

Numerical Analysis · Mathematics 2023-11-08 Ben Adcock , Simone Brugiapaglia , Nick Dexter , Sebastian Moraga

We provide a comprehensive study of interrelations between different measures of smoothness of functions on various domains and smoothness properties of approximation processes. Two general approaches to this problem have been developed:…

Classical Analysis and ODEs · Mathematics 2020-03-18 Yu. Kolomoitsev , S. Tikhonov

We discuss the notion of optimal polynomial approximants in multivariable reproducing kernel Hilbert spaces. In particular, we analyze difficulties that arise in the multivariable case which are not present in one variable, for example, a…

Complex Variables · Mathematics 2022-05-03 Meredith Sargent , Alan Sola

In this paper we prove an analogue of the discrete spherical maximal theorem of Magyar, Stein, and Wainger, an analogue which concerns maximal functions associated to homogenous algebraic surfaces. Let $\mathfrak{p}$ be a homogenous…

Number Theory · Mathematics 2017-12-06 Brian Cook

We propose a new algorithm that finds an $\varepsilon$-approximate fixed point of a smooth function from the $n$-dimensional $\ell_2$ unit ball to itself. We use the general framework of finding approximate solutions to a variational…

Computer Science and Game Theory · Computer Science 2025-01-22 Idan Attias , Yuval Dagan , Constantinos Daskalakis , Rui Yao , Manolis Zampetakis

Let $({\mathcal X}, d, \mu)$ be a metric measure space and satisfy the so-called upper doubling condition and the geometrical doubling condition. In this paper, we introduce the atomic Hardy space $H^1(\mu)$ and prove that its dual space is…

Classical Analysis and ODEs · Mathematics 2015-05-19 Tuomas Hytönen , Dachun Yang , Dongyong Yang

We examine the necessary and sufficient complexity of neural networks to approximate functions from different smoothness spaces under the restriction of encodable network weights. Based on an entropy argument, we start by proving lower…

Functional Analysis · Mathematics 2020-09-21 Ingo Gühring , Mones Raslan
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