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We study best approximation to a given function, in the least square sense on a subset of the unit circle, by polynomials of given degree which are pointwise bounded on the complementary subset. We show that the solution to this problem, as…

Functional Analysis · Mathematics 2017-10-31 L Baratchart , Juliette Leblond , Fabien Seyfert

We provide sharp bounds for the exponential moments and $p$-moments, $1\leqslant p \leqslant 2$, of the terminate distribution of a martingale whose square function is uniformly bounded by one. We introduce a Bellman function for the…

Probability · Mathematics 2022-08-09 Dmitriy Stolyarov , Vasily Vasyunin , Pavel Zatitskiy , Ilya Zlotnikov

The optimal pair of two linear varieties is considered as a best approximation problem, namely the distance between a point and the difference set of two linear varieties. The Gram determinant allows to get the optimal pair in closed form.

Metric Geometry · Mathematics 2016-11-25 Armando Gonçalves , M. A. Facas Vicente , José Vitória

We investigate numerical differentiation formulas on irregular centers in two or more variables that are exact for polynomials of a given order and minimize an absolute seminorm of the weight vector. Error bounds are given in terms of a…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov , Robert Schaback

This paper mainly addresses the optimization of $p$-th moment of $\mathbb{R}^n$-valued random variable. Through an ingenious approximation mechanism, one transforms the maximization problem into a sequence of minimization problems, which…

Optimization and Control · Mathematics 2016-07-26 Xiaojun Lu , Yanhua Wu

Approximating a convex function by a polyhedral function that has a limited number of facets is a fundamental problem with applications in various fields, from mitigating the curse of dimensionality in optimal control to bi-level…

Optimization and Control · Mathematics 2025-09-05 Abdellah Bulaich Mehamdi , Wim van Ackooij , Luce Brotcorne , Stéphane Gaubert , Quentin Jacquet

The problem of root mean square approximation of a square integrable function by finite linear combinations of exponential functions is considered. It is subdivided into linear and nonlinear parts. The linear approximation problem is…

Classical Analysis and ODEs · Mathematics 2014-11-11 Ruslan Sharipov

Dual feasible functions (DFFs) have been used to provide bounds for standard packing problems and valid inequalities for integer optimization problems. In this paper, the connection between general DFFs and a particular family of…

Optimization and Control · Mathematics 2018-12-04 Matthias Köppe , Jiawei Wang

To estimate the optimal constant in Hardy-type inequalities, some variational formulas and approximating procedures are introduced. The known basic estimates are improved considerably. The results are illustrated by typical examples. It is…

Probability · Mathematics 2015-01-15 Mu-Fa Chen

The Bell inequalities in three and four correlations are re-derived in general forms showing that three and four data sets, respectively, identically satisfy them regardless of whether they are random, deterministic, measured, predicted, or…

Quantum Physics · Physics 2020-06-24 Louis Sica

The general properties of two-dimensional generalized Bessel functions are discussed. Various asymptotic approximations are derived and applied to analyze the basic structure of the two-dimensional Bessel functions as well as their nodal…

Quantum Physics · Physics 2008-08-12 H. J. Korsch , A. Klumpp , D. Witthaut

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

We present an algorithm to approximate the solutions to variational problems where set of admissible functions consists of convex functions. The main motivator behind this numerical method is estimating solutions to Adverse Selection…

Optimization and Control · Mathematics 2008-03-07 Ivar Ekeland , Santiago Moreno

The paper is about developing a solver for maximizing a real-valued function of binary variables. The solver relies on an algorithm that estimates the optimal objective-function value of instances from the underlying distribution of…

Machine Learning · Computer Science 2025-11-05 Nimrod Megiddo , Segev Wasserkrug , Orit Davidovich , Shimrit Shtern

John Bell showed that a big class of local hidden-variable models stands in conflict with quantum mechanics and experiment. Recently, there were suggestions that empirical adequate hidden-variable models might exist, which presuppose a…

Quantum Physics · Physics 2007-05-23 Gerd Grasshoff , Samuel Portmann , Adrian Wuethrich

We derive both numerically and analytically Bell inequalities and quantum measurements that present enhanced resistance to detector inefficiency. In particular we describe several Bell inequalities which appear to be optimal with respect to…

Quantum Physics · Physics 2007-10-22 Serge Massar , Stefano Pironio , Jeremie Roland , Bernard Gisin

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

This work investigates a new approach to find closed form analytical approximate solution of linear initial value problems. Classical Bernoulli polynomials have been used to derive a finite set of orthonormal polynomials and a finite…

Numerical Analysis · Mathematics 2020-07-27 Udaya Pratap Singh

In this article, we provide a comprehensive analysis of the asymptotic behavior of Bell numbers, enhancing and unifying various results previously dispersed in the literature. We establish several explicit lower and upper bounds. The main…

Number Theory · Mathematics 2024-08-27 Jerzy Grunwald , Grzegorz Serafin

This paper considers pairs of optimization problems that are defined from a single input and for which it is desired to find a good approximation to either one of the problems. In many instances, it is possible to efficiently find an…

Data Structures and Algorithms · Computer Science 2009-09-11 David Eppstein