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In this survey, we discuss volumetric and combinatorial results concerning (mostly finite) intersections or unions of balls (mostly of equal radii) in the $d$-dimensional real vector space, mostly equipped with the Euclidean norm. Our first…

Metric Geometry · Mathematics 2025-12-30 Károly Bezdek , Zsolt Lángi , Márton Naszódi

Recent studies revealed the mathematical connection of deep neural network (DNN) and dynamic system. However, the fundamental principle of DNN has not been fully characterized with dynamic system in terms of optimization and generalization.…

Machine Learning · Computer Science 2021-03-05 Kuo Gai , Shihua Zhang

This note attempts to revisit the classical results on Laplace approximation in a modern non-asymptotic and dimension free form. Such an extension is motivated by applications to high dimensional statistical and optimization problems. The…

Statistics Theory · Mathematics 2022-12-13 Vladimir Spokoiny

This document offers a concise introduction to the mathematical theory and practical application of the Hausdorff Measure and Dimension. The primary objective is to clarify and rigorously detail the two most common methods used for…

History and Overview · Mathematics 2025-11-20 Umberto Michelucci

We prove that for any proper metric space $X$ and a function $\psi:(0,\infty)\to(0,\infty)$ from a suitable class of approximation functions, the Hausdorff dimensions of the set $W_\psi(Q)$ of all points $\psi$-well-approximable by a…

Number Theory · Mathematics 2022-08-31 Prasuna Bandi , Anish Ghosh , Debanjan Nandi

We show that lower-dimensional marginal densities of dependent zero-mean normal distributions truncated to the positive orthant exhibit a mass-shifting phenomenon. Despite the truncated multivariate normal density having a mode at the…

Statistics Theory · Mathematics 2020-05-20 Shuang Zhou , Pallavi Ray , Debdeep Pati , Anirban Bhattacharya

The Hausdorff dimension of the set of points that are covered infinitely many times by a sequence of randomly distributed balls in the unit cube can be expressed in terms of the sizes of the balls. This note presents a new proof of the…

Classical Analysis and ODEs · Mathematics 2019-10-29 Fredrik Ekström

One of the fundamental problems in Bayesian statistics is the approximation of the posterior distribution. Gibbs sampler and coordinate ascent variational inference are renownedly utilized approximation techniques that rely on stochastic…

Statistics Theory · Mathematics 2021-06-18 Se Yoon Lee

In 1926 Khintchine introduced a topological argument proving the existence of uncountably many nontrivial singular linear forms of $n \geq 2$ variables. Throughout the years, this argument has been extensively modified and generalized. Most…

Number Theory · Mathematics 2026-03-30 Leo Hong , Dmitry Kleinbock , Vasiliy Neckrasov

The Generalised Baker-Schmidt Problem (1970) concerns the Hausdorff measure of the set of $\psi$-approximable points on a nondegenerate manifold. Beresnevich-Dickinson-Velani (in 2006, for the homogeneous setting) and…

Number Theory · Mathematics 2026-05-08 Mumtaz Hussain , Johannes Schleischitz , Benjamin Ward

We provide a closed formula of Bowen type for the Hausdorff dimension of a very general shrinking target scheme generated by the non-autonomous dynamical system on the interval $[0,1)$, viewed as $\mathbb{R}/\mathbb{Z}$, corresponding to a…

Dynamical Systems · Mathematics 2015-09-08 Lior Fishman , Bill Mance , David Simmons , Mariusz Urbanski

This paper develops a general theory for first-order descent methods whose search directions are restricted to a prescribed dictionary in a reflexive Banach space. Instead of assuming that the linear span of the dictionary is dense, as in…

Optimization and Control · Mathematics 2026-03-13 Miguel Berasategui , Pablo M. Berná , Antonio Falcó

We consider the dynamics of thin two-dimensional viscous droplets on chemically heterogeneous surfaces moving under the combined effects of slip, mass transfer and capillarity. The resulting long-wave evolution equation for the droplet…

Fluid Dynamics · Physics 2021-12-20 Danny Groves , Nikos Savva

The variational principle of minimum free energy (MFEVP) has been widely used in the study of soft matter statics. MFEVP can be used not only to derive equilibrium equations (including both bulk equations and boundary conditions), but also…

Soft Condensed Matter · Physics 2022-10-12 Haiqin Wang , Xinpeng Xu

We introduce and develop a class of \textit{Cantor-winning} sets that share the same amenable properties as the classical winning sets associated to Schmidt's $(\alpha,\beta)$-game: these include maximal Hausdorff dimension, invariance…

Number Theory · Mathematics 2015-09-09 Dzmitry Badziahin , Stephen Harrap

In the standard formulation of the occupancy problem one considers the distribution of r balls in n cells, with each ball assigned independently to a given cell with probability 1/n. Although closed form expressions can be given for the…

Probability · Mathematics 2007-05-23 Paul Dupuis , Carl Nuzman , Phil Whiting

In this paper we consider a multiparametric version of Wolfgang Schmidt and Leonard Summerer's parametric geometry of numbers. We apply this approach in two settings: the first one concerns weighted Diophantine approximation, the second one…

Number Theory · Mathematics 2021-07-20 Oleg N. German

The number of lattice points in $d$-dimensional hyperbolic or elliptic shells $\{m : a<Q[m]<b\}$, which are restricted to rescaled and growing domains $r\;\Omega$, is approximated by the volume. An effective error bound of order…

Number Theory · Mathematics 2021-11-16 Paul Buterus , Friedrich Götze , Thomas Hille , Gregory Margulis

The present paper establishes upper and lower bounds on the speed of approximation in a wide range of natural Diophantine approximation problems. The upper and lower bounds coincide in many cases, giving rise to optimal results in…

Number Theory · Mathematics 2014-07-11 Anish Ghosh , Alex Gorodnik , Amos Nevo

Data-dependent metrics are powerful tools for learning the underlying structure of high-dimensional data. This article develops and analyzes a data-dependent metric known as diffusion state distance (DSD), which compares points using a…

Machine Learning · Statistics 2020-03-10 Lenore Cowen , Kapil Devkota , Xiaozhe Hu , James M. Murphy , Kaiyi Wu