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We seek random versions of some classical theorems on complex approximation by polynomials and rational functions, as well as investigate properties of random compact sets in connection to complex approximation.

Complex Variables · Mathematics 2017-09-26 Simon St-Amant , Jérémie Turcotte

This paper offers a mathematical invention that shows how to convert integrated quantiles, which often appear in risk measures, into integrated cumulative distribution functions, which are technically more tractable from various…

Risk Management · Quantitative Finance 2023-04-26 Yunran Wei , Ricardas Zitikis

Abstract convexity generalises classical convexity by considering the suprema of functions taken from an arbitrarily defined set of functions. These are called the abstract linear (abstract affine) functions. The purpose of this paper is to…

Optimization and Control · Mathematics 2025-01-30 Reinier Diàz Millàn , Nadezda Sukhorukova , Julien Ugon

We establish a result which states that regularizing an inverse problem with the gauge of a convex set $C$ yields solutions which are linear combinations of a few extreme points or elements of the extreme rays of $C$. These can be…

Optimization and Control · Mathematics 2018-12-12 Claire Boyer , Antonin Chambolle , Yohann de Castro , Vincent Duval , Frédéric de Gournay , Pierre Weiss

We give an explicit sequence of polarizations such that for every measurable function, the sequence of iterated polarizations converge to the symmetric rearrangement of the initial function.

Functional Analysis · Mathematics 2009-12-22 Jean Van Schaftingen

L$^\natural$ (natural)-convex functions encompass a large class of nonlinear functions over general integer domains and arise in a wide range of real-world applications. We explore the minimization of L$^\natural$-convex functions, of…

Optimization and Control · Mathematics 2025-11-26 Qimeng Yu , Simge Küçükyavuz

Tame functions are a class of nonsmooth, nonconvex functions, which feature in a wide range of applications: functions encountered in the training of deep neural networks with all common activations, value functions of mixed-integer…

Optimization and Control · Mathematics 2024-06-05 Gilles Bareilles , Johannes Aspman , Jiri Nemecek , Jakub Marecek

The aim of this paper is twofold: In the first part, we leverage recent results on scenario design to develop randomized algorithmsfor approximating the image set of a nonlinear mapping, that is, a (possibly noisy) mapping of a set via a…

Optimization and Control · Mathematics 2015-07-30 Fabrizio Dabbene , Didier Henrion , Constantino Lagoa , Pavel Shcherbakov

Integral transforms are invaluable mathematical tools to map functions into spaces where they are easier to characterize. We introduce the hyperdimensional transform as a new kind of integral transform. It converts square-integrable…

Machine Learning · Computer Science 2023-10-26 Pieter Dewulf , Michiel Stock , Bernard De Baets

In this article, we define a matrix multinomial distribution. We prove some properties of the matrix multinomial distribution. We prove that the matrix Poisson distribution can be used as an approximation to the matrix multinomial…

Probability · Mathematics 2021-04-30 Yuriy Yurchenko

We consider the infinite symmetric group and its infinite index subgroup given as the stabilizer subgroup of one element under the natural action on a countable set. This inclusion of discrete groups induces a hyperfinite subfactor for each…

Operator Algebras · Mathematics 2013-05-06 Makoto Yamashita

We identity the optimal non-infinitesimal direction of descent for a convex function. An algorithm is developed that can theoretically minimize a subset of (non-convex) functions.

Optimization and Control · Mathematics 2025-09-19 Andrew J. Young

We consider four prototypes of variational problems and prove the existence of fractal minimizers through the direct method in the calculus of variations. By design these minimizers are H\"older curves or H\"older parametrizations of…

Probability · Mathematics 2025-12-17 Michael Hinz , Jonas M. Tölle , Lauri Viitasaari

In order to investigate minimal sufficient conditions for an abstract integral to belong to the convex hull of the integrand, we propose a system of axioms under which it happens. If the integrand is a continuous $R^n$-valued function over…

Probability · Mathematics 2015-06-19 Milan Merkle

We characterize the mixed discriminant of positive semi definite matrices using its most basic properties. As a corollary we establish its minimality among non negative and multi additive functionals.

Functional Analysis · Mathematics 2013-09-20 D. I. Florentin , V. D. Milman , R. Schneider

We consider the space of real-valued continuously differentiable functions on a compact subset of a euclidean space. We characterize the completeness of this space and prove that the space of restrictions of continuously differentiable…

Classical Analysis and ODEs · Mathematics 2020-06-18 Leonhard Frerick , Laurent Loosveldt , Jochen Wengenroth

We develop a version of Herbrand's theorem for continuous logic and use it to prove that definable functions in infinite-dimensional Hilbert spaces are piecewise approximable by affine functions. We obtain similar results for definable…

Logic · Mathematics 2011-07-20 Isaac Goldbring

The notion of Schnorr randomness refers to computable reals or computable functions. We propose a version of Schnorr randomness for subcomputable classes and characterize it in different ways: by Martin L\"of tests, martingales or measure…

Logic in Computer Science · Computer Science 2019-03-14 Claude Sureson

We characterize left and right amenable semigroups of polynomials of one complex variable with respect to the composition operation. We also prove a number of results about amenable semigroups of arbitrary rational functions. In particular,…

Dynamical Systems · Mathematics 2021-08-25 Fedor Pakovich

An invex function generalizes a convex function in the sense that every stationary point is a global minimizer. Recently, invex functions and their subclasses have attracted attention in signal processing and machine learning. However,…

Optimization and Control · Mathematics 2026-04-06 Akatsuki Nishioka