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For a real-valued function $f$ on a metric measure space $(X,d,\mu)$ the Hardy-Littlewood maximal-function of $f$ is given by the following `supremum-norm':…

Functional Analysis · Mathematics 2023-01-18 Maysam Maysami Sadr

This paper investigates the numerical approximation of integrals for functions in fractional Gaussian Sobolev spaces $W^s_{p}(\mathbb{R}^d,\gamma)$ with dominating mixed smoothness defined via kernel related to the fractional…

Numerical Analysis · Mathematics 2026-04-21 Van Kien Nguyen

Error bounds and complexity bounds in numerical analysis and information-based complexity are often proved for functions that are defined on very simple domains, such as a cube, a torus, or a sphere. We study optimal error bounds for the…

Numerical Analysis · Mathematics 2020-01-15 Erich Novak

In this paper, we specify a set of optimal subspaces for $L_2$ approximation of three classes of functions in the Sobolev space $W^{(r)}_2$, defined on a segment and subject to certain boundary conditions. All of these subspaces are…

Classical Analysis and ODEs · Mathematics 2019-05-28 A. Yu. Ulitskaya , O. L. Vinogradov

High-order derivatives of analytic functions are expressible as Cauchy integrals over circular contours, which can very effectively be approximated, e.g., by trapezoidal sums. Whereas analytically each radius r up to the radius of…

Numerical Analysis · Mathematics 2011-04-04 Folkmar Bornemann

For various Hilbert spaces of analytic functions on the unit disk, we characterize when a function $f$ has optimal polynomial approximants given by truncations of a single power series. We also introduce a generalized notion of optimal…

Functional Analysis · Mathematics 2023-07-11 Christopher Felder

We discuss approximation of extremal functions by polynomials in the weighted Bergman spaces $A^p_\alpha$ where $-1 < \alpha < 0$ and $-1 < \alpha < p-2$. We obtain bounds on how close the approximation is to the true extremal function in…

Complex Variables · Mathematics 2017-05-19 Timothy Ferguson

This paper presents a polynomial-time $1/2$-approximation algorithm for maximizing nonnegative $k$-submodular functions. This improves upon the previous $\max\{1/3, 1/(1+a)\}$-approximation by Ward and \v{Z}ivn\'y~(SODA'14), where…

Data Structures and Algorithms · Computer Science 2015-02-27 Satoru Iwata , Shin-ichi Tanigawa , Yuichi Yoshida

We provide a general framework to construct finite dimensional approximations of the space of convex functions, which also applies to the space of c-convex functions and to the space of support functions of convex bodies. We give estimates…

Numerical Analysis · Mathematics 2014-03-11 Quentin Mérigot , Edouard Oudet

In this note we present a version of Hardy's inequality on a measure space $(X,\mu)$ endowed with a measurable function $N\colon X\to \mathbb R$ which replaces the absolute value on $\mathbb R$ or $\mathbb R^n$, and, more generally, the…

Functional Analysis · Mathematics 2023-03-20 Mattia Calzi

This is a continuation of our earlier paper \cite{PT3}. We consider here operator-valued functions (or infinite matrix functions) on the unit circle $\T$ and study the problem of approximation by bounded analytic operator functions. We…

Functional Analysis · Mathematics 2007-05-23 V. V. Peller , S. R. Treil

We study some approximation problems on a strict subset of the circle by analytic functions of the Hardy space H2 of the unit disk (in C), whose modulus satisfy a pointwise constraint on the complentary part of the circle. Existence and…

Functional Analysis · Mathematics 2009-11-10 Laurent Baratchart , Juliette Leblond , Fabien Seyfert

This is a survey on best polynomial approximation on the unit sphere and the unit ball. The central problem is to describe the approximation behavior of a function by polynomials via smoothness of the function. A major effort is to identify…

Classical Analysis and ODEs · Mathematics 2014-02-25 Yuan Xu

Let ${\mathcal X}$ be an RD-space with $\mu({\mathcal X})=\infty$, which means that ${\mathcal X}$ is a space of homogeneous type in the sense of Coifman and Weiss and its measure has the reverse doubling property. In this paper, we…

Classical Analysis and ODEs · Mathematics 2009-08-31 Dachun Yang , Yuan Zhou

We study approximation by arbitrary linear combinations of $n$ translates of a single function of periodic functions. We construct some methods of this approximation for functions in a class induced by the convolution with a given function,…

Numerical Analysis · Mathematics 2017-03-01 Dinh Dũng , Charles A. Micchelli , Vu Nhat Huy

Most commonly used \emph{adaptive} algorithms for univariate real-valued function approximation and global minimization lack theoretical guarantees. Our new locally adaptive algorithms are guaranteed to provide answers that satisfy a…

Numerical Analysis · Mathematics 2017-08-28 Sou-Cheng T. Choi , Yuhan Ding , Fred J. Hickernell , Xin Tong

We study approximation of functions by algebraic polynomials in the H\"older spaces corresponding to the generalized Jacobi translation and the Ditzian-Totik moduli of smoothness. By using modifications of the classical moduli of…

Classical Analysis and ODEs · Mathematics 2016-02-17 Yurii Kolomoitsev , Tetiana Lomako , Jürgen Prestin

We consider discrete optimization problems with interval uncertatinty of objective function coefficients. The interval uncertainty models measurements errors. A pos\-sible optimal solution is a solution that is optimal for some possible…

Optimization and Control · Mathematics 2022-06-22 Alexander Prolubnikov

The challenge of approximating functions in infinite-dimensional spaces from finite samples is widely regarded as formidable. We delve into the challenging problem of the numerical approximation of Sobolev-smooth functions defined on…

Optimization and Control · Mathematics 2024-10-11 Massimo Fornasier , Pascal Heid , Giacomo Enrico Sodini

Submodular continuous functions are a category of (generally) non-convex/non-concave functions with a wide spectrum of applications. We characterize these functions and demonstrate that they can be maximized efficiently with approximation…

Machine Learning · Computer Science 2019-05-07 Andrew An Bian , Baharan Mirzasoleiman , Joachim M. Buhmann , Andreas Krause