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We prove that intersections and unions of independent random sets in finite spaces achieve a form of Lipschitz continuity. More precisely, given the distribution of a random set $\Xi$, the function mapping any random set distribution to the…

Other Statistics · Statistics 2020-03-03 John Klein

The escaping set I(f) of a transcendental meromorphic function f consists of all points which tend to infinity under iteration. The Eremenko-Lyubich class B consists of all transcendental meromorphic functions for which the set of finite…

Dynamical Systems · Mathematics 2012-08-13 Walter Bergweiler , Janina Kotus

Following the development of weighted asymptotic approximation properties of matrices, we introduce the analogous uniform approximation properties (that is, study the improvability of Dirichlet's Theorem). An added feature is the use of…

Number Theory · Mathematics 2022-02-25 Dmitry Kleinbock , Anurag Rao

For the positive solutions of the competitive Gross-Pitaevskii system of two equations, we prove that L^\infty boundedness implies uniform H\"older boundedness as the competition parameter goes to infinity. Moreover we prove that the…

Analysis of PDEs · Mathematics 2008-10-31 Benedetta Noris , Hugo Tavares , Susanna Terracini , Gianmaria Verzini

Let A be a bounded subset of IR^d. We give an upper bound on the volume of the symmetric difference of A and f(A) where f is a translation, a rotation, or the composition of both, a rigid motion. The volume is measured by the d-dimensional…

Metric Geometry · Mathematics 2010-10-13 Daria Schymura

The notions of unimodular Minkowski and Hausdorff dimensions are defined in [arXiv:1807.02980] for unimodular random discrete metric spaces. The present paper is focused on the connections between these notions and the polynomial growth…

Probability · Mathematics 2021-02-16 François Baccelli , Mir-Omid Haji-Mirsadeghi , Ali Khezeli

We consider a class of attractive-repulsive energies, given by the sum of two nonlocal interactions with power-law kernels, defined over sets with fixed measure. It has recently been proved by R. Frank and E. Lieb that the ball is the…

Analysis of PDEs · Mathematics 2024-01-12 Marco Bonacini , Riccardo Cristoferi , Ihsan Topaloglu

In this paper, we generalize the usual notions of waves, fronts and propagation speeds in a very general setting. These new notions, which cover all classical situations, involve uniform limits, with respect to the geodesic distance, to a…

Analysis of PDEs · Mathematics 2010-12-06 Henri Berestycki , François Hamel

Let $\Omega \subset \mathbb{R}^2$ be a bounded convex domain. Steinerberger (2026) introduced the Buffon discrepancy problem: given length $L$, construct a one-dimensional set $S\subset\Omega$ such that the number of intersections of $S$…

Combinatorics · Mathematics 2026-05-12 Samuel Korsky

In this paper, we study the topological entropy and the Hausdorff dimension of a shrinking target set. We give lower and upper bounds of topological entropy and Hausdorff dimension for dynamical systems with exponential specification…

Dynamical Systems · Mathematics 2024-10-29 Xiaobo Hou , Xueting Tian , Yiwei Zhang

We study generalizations of Reifenberg's Theorem for measures in $\mathbb R^n$ under assumptions on the Jones' $\beta$-numbers, which appropriately measure how close the support is to being contained in a subspace. Our main results, which…

Classical Analysis and ODEs · Mathematics 2025-03-25 Nick Edelen , Aaron Naber , Daniele Valtorta

We study two closely related problems stemming from the random wave conjecture for Maass forms. The first problem is bounding the $L^4$-norm of a Maass form in the large eigenvalue limit; we complete the work of Spinu to show that the…

Number Theory · Mathematics 2018-11-06 Peter Humphries

We establish sharp bounds for the Hausdorff dimension of sets of irrational numbers in $(0,1)$ whose digits in the $N$-expansion are either uniformly bounded or tend to infinity. For sets with digits bounded by an integer $M \ge N$, we…

Number Theory · Mathematics 2026-03-31 Andreea Catalina Chitu , Gabriela Ileana Sebe , Dan Lascu

One of our main goals in this paper is to understand the behavior of limit sets of a diverging sequence of Schottky groups in the group of isometries of the N-dimensional hyperbolic space. This leads us to a generalization of a classical…

Dynamical Systems · Mathematics 2024-10-15 Antonin Guilloux , Gilles Courtois

The Hausdorff distance is a measure of (dis-)similarity between two sets which is widely used in various applications. Most of the applied literature is devoted to the computation for sets consisting of a finite number of points. This has…

Metric Geometry · Mathematics 2020-09-22 Daniel Kraft

The notions of shyness and prevalence generalize the property of being zero and full Haar measure to arbitrary (not necessarily locally compact) Polish groups. The main goal of the paper is to answer the following question: What can we say…

Classical Analysis and ODEs · Mathematics 2016-08-02 Richárd Balka , Udayan B. Darji , Márton Elekes

Theorems of Khintchine, Groshev, Jarn\'ik, and Besicovitch in Diophantine approximation are fundamental results on the metric properties of $\Psi$-well approximable sets. These foundational results have since been generalised to the…

Number Theory · Mathematics 2025-07-09 Gerardo González Robert , Mumtaz Hussain , Nikita Shulga , Benjamin Ward

Based on the isoperimetric inequality, G. Huisken proposed a definition of total mass in general relativity that is equivalent to the ADM mass for (smooth) asymptotically flat 3-manifolds of nonnegative scalar curvature, but that is…

Differential Geometry · Mathematics 2020-02-21 Jeffrey L. Jauregui

We provide a new upper bound for sampling numbers $(g_n)_{n\in \mathbb{N}}$ associated to the compact embedding of a separable reproducing kernel Hilbert space into the space of square integrable functions. There are universal constants…

Numerical Analysis · Mathematics 2021-02-11 Nicolas Nagel , Martin Schäfer , Tino Ullrich

In transfer learning, training and testing data sets are drawn from different data distributions. The transfer generalization gap is the difference between the population loss on the target data distribution and the training loss. The…

Machine Learning · Computer Science 2021-01-26 Sharu Theresa Jose , Osvaldo Simeone
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