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A monotone function interval is the set of monotone functions that lie pointwise between two fixed monotone functions. We characterize the set of extreme points of monotone function intervals and apply this to a number of economic settings.…

Theoretical Economics · Economics 2024-04-16 Kai Hao Yang , Alexander K. Zentefis

Subadditive set functions play a pivotal role in computational economics (especially in combinatorial auctions), combinatorial optimization or artificial intelligence applications such as interpretable machine learning. However, specifying…

Machine Learning · Computer Science 2026-03-12 Martin Černý , David Sychrovský , Filip Úradník , Jakub Černý

Quantitative formulations of Fefferman's counterexample for the ball multiplier are naturally linked to square function and vector-valued estimates for directional singular integrals. The latter are usually referred to as Meyer-type lemmas…

Classical Analysis and ODEs · Mathematics 2020-04-16 Francesco Di Plinio , Ioannis Parissis

In this paper, we describe an algorithm for approximating functions of the form $f(x)=\int_{a}^{b} x^{\mu} \sigma(\mu) \, d \mu$ over $[0,1]$, where $\sigma(\mu)$ is some signed Radon measure, or, more generally, of the form $f(x) =…

Numerical Analysis · Mathematics 2024-12-10 Mohan Zhao , Kirill Serkh

In this paper, we study the problem of pointwise estimation of a multivariate function. We develop a general pointwise estimation procedure that is based on selection of estimators from a large parameterized collection. An upper bound on…

Statistics Theory · Mathematics 2008-11-18 Alexander Goldenshluger , Oleg Lepski

In many practical applications, spatial data are often collected at areal levels (i.e., block data) and the inferences and predictions about the variable at points or blocks different from those at which it has been observed typically…

Computation · Statistics 2020-01-10 Peter Simonson , Douglas Nychka , Soutir Bandyopadhyay

We investigated the asymptotics of high-rate constrained quantization errors for a compactly supported probability measure P on Euclidean spaces whose quantizers are confined to a closed set S. The key tool is the metric projection of K…

Metric Geometry · Mathematics 2025-05-19 Chenxing Qian

The aim of this paper is to characterize a fractal operator associated with multivariate fractal interpolation functions (FIFs) and study the several properties of this fractal operator. Further, with the help of this operator, we…

Dynamical Systems · Mathematics 2023-10-20 Amit Bawalia , Vineeta Basotia , Ajay Prajapati

We study multivariate integration and approximation for functions belonging to a weighted reproducing kernel Hilbert space based on half-period cosine functions in the worst-case setting. The weights in the norm of the function space depend…

Numerical Analysis · Mathematics 2015-11-23 Christian Irrgeher , Peter Kritzer , Friedrich Pillichshammer

This article deals with the lower compactness property of a sequence of integrands and the use of this key notion in various domains: convergence theory, optimal control, non-smooth analysis. First about the interchange of the weak…

Optimization and Control · Mathematics 2015-06-22 Emmanuel Giner

We prove that the smallest minimizer s(f) of a real convex function f is less than or equal to a real point x if and only if the right derivative of f at x is non-negative. Similarly, the largest minimizer t(f) is greater or equal to x if…

Probability · Mathematics 2023-11-07 Dietmar Ferger

We establish presumably optimal rates of normal convergence with respect to the Kolmogorov distance for a large class of geometric functionals of marked Poisson and binomial point processes on general metric spaces. The rates are valid…

Probability · Mathematics 2017-02-03 Raphaël Lachièze-Rey , Matthias Schulte , J. E. Yukich

Following the ideas from a paper by the same author, we prove abstract maximal restriction results for the Fourier transform. Our results deal mainly with maximal operators of convolution-type and $r-$average maximal functions. As a…

Classical Analysis and ODEs · Mathematics 2019-04-25 João Pedro Ramos

A jump system is defined as a set of integer points (vectors) with a certain exchange property, generalizing the concepts of matroids, delta-matroids, and base polyhedra of integral polymatroids (or submodular systems). A discrete convexity…

Combinatorics · Mathematics 2020-09-21 Kazuo Murota

We reconstruct the velocity field of incompressible flows given a finite set of measurements. For the spatial approximation, we introduce the Sparse Fourier divergence-free (SFdf) approximation based on a discrete $L^2$ projection. Within…

Fluid Dynamics · Physics 2021-10-13 Luis Espath , Dmitry Kabanov , Jonas Kiessling , Raúl Tempone

We strengthen the classical approximation theorems of Weierstrass, Runge and Mergelyan by showing the polynomial and rational approximants can be taken to have a simple geometric structure. In particular, when approximating a function $f$…

Complex Variables · Mathematics 2023-02-14 Christopher J. Bishop , Kirill Lazebnik

Let the metric space $\mathbb R^n \setminus \sim$ be the metric space of $n$-sized unordered tuples of real numbers. In the following, it will be shown that if a function $\varphi: \mathbb R^m \to \mathbb R^n \setminus \sim$ is continuous,…

Metric Geometry · Mathematics 2014-06-24 Adrian Fellhauer

We apply upper and lower compensated convex transforms, which are `tight' one-sided approximations of a given function, to the extraction of fine geometric singularities from semiconvex/semiconcave functions and DC-functions in…

Optimization and Control · Mathematics 2016-10-06 Kewei Zhang , Elaine Crooks , Antonio Orlando

We generalize some classical results about quasicontinuous and separately continuous functions with values in metrizable spaces to functions with values in certain generalized metric spaces, called Maslyuchenko spaces. We establish…

General Topology · Mathematics 2021-11-01 Taras Banakh

We study universal approximation of continuous functionals on compact subsets of products of Hilbert spaces. We prove that any such functional can be uniformly approximated by models that first take finitely many continuous linear…

Machine Learning · Computer Science 2026-02-04 Andrey Krylov , Maksim Penkin