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Functionals in geometric probability are often expressed as sums of bounded functions exhibiting exponential stabilization. Methods based on cumulant techniques and exponential modifications of measures show that such functionals satisfy…

Probability · Mathematics 2009-09-29 Yu Baryshnikov , P. Eichelsbacher , T. Schreiber , J. E. Yukich

In this paper, we propose the Fourier Discrepancy Function, a new discrepancy to compare discrete probability measures. We show that this discrepancy takes into account the geometry of the underlying space. We prove that the Fourier…

Machine Learning · Statistics 2021-11-19 Auricchio Gennaro , Codegoni Andrea , Gualandi Stefano , Zambon Lorenzo

Mixture distributions are extensively used as a modeling tool in diverse areas from machine learning to communications engineering to physics, and obtaining bounds on the entropy of probability distributions is of fundamental importance in…

Information Theory · Computer Science 2022-12-05 James Melbourne , Saurav Talukdar , Shreyas Bhaban , Mokshay Madiman , Murti V. Salapaka

This paper addresses the statistical problem of estimating the infinite-norm deviation from the empirical mean to the distribution mean for high-dimensional distributions on $\{0,1\}^d$, potentially with $d=\infty$. Unlike traditional…

Statistics Theory · Mathematics 2024-02-21 Moïse Blanchard , Václav Voráček

In the absence of a unique, gauge-independent definition of eccentricity in General Relativity, there have been efforts to standardize the definition for Gravitational-Wave astronomy. Recently, Shaikh et al. proposed a model-independent…

General Relativity and Quantum Cosmology · Physics 2025-04-02 Nicolas Chartier , Md Arif Shaikh , Hyung Mok Lee , JeongCho Kim

Discrepancy is a well-known measure for the irregularity of the distribution of a point set. Point sets with small discrepancy are called low-discrepancy and are known to efficiently fill the space in a uniform manner. Low-discrepancy…

Machine Learning · Computer Science 2024-09-27 T. Konstantin Rusch , Nathan Kirk , Michael M. Bronstein , Christiane Lemieux , Daniela Rus

The one-particle distribution function is of importance both in non-relativistic and relativistic statistical physics. In the relativistic framework, Lorentz invariance is possibly its most fundamental property. The present article on the…

Astrophysics · Physics 2009-06-23 Fabrice Debbasch , Jean-Pierre Rivet , Willem Van Leeuwen

We characterize the limiting behavior of partial sums of multiplicative functions $f:\mathbb{F}_q[t]\to S^1$. In contrast to the number field setting, the characterization depends crucially on whether the notion of discrepancy is defined…

Number Theory · Mathematics 2024-08-19 Oleksiy Klurman , Alexander P. Mangerel , Joni Teräväinen

The present paper contains additional asymptotic result over an earlier investigation of Kapelko and Kranakis. Consider $n$ mobile sensors placed independently at random with the uniform distribution on the unit interval $[0,1]$. Fix $a$ an…

Discrete Mathematics · Computer Science 2018-04-24 Rafał Kapelko

We generalize the well-known mixtures of Gaussians approach to density estimation and the accompanying Expectation--Maximization technique for finding the maximum likelihood parameters of the mixture to the case where each data point…

Methodology · Statistics 2011-08-01 Jo Bovy , David W. Hogg , Sam T. Roweis

The L infinity star discrepancy is a measure for how uniformly a point set is distributed in a given space. Point sets of low star discrepancy are used as designs of experiments, as initial designs for Bayesian optimization algorithms, for…

Neural and Evolutionary Computing · Computer Science 2026-04-02 Imène Ait Abderrahim , Carola Doerr , Martin Durand

We discuss some surprising phenomena from basic calculus related to oscillating functions and to the theorem on the differentiability of inverse functions. Among other things, we see that a continuously differentiable function with a strict…

History and Overview · Mathematics 2016-09-29 Juergen Grahl , Shahar Nevo

We show that if an essentially arbitrary sequence supported on an interval containing $x$ integers, is convolved with a tiny Siegel-Walfisz-type sequence supported on an interval containing $\exp((\log x)^{\varepsilon})$ integers then the…

Number Theory · Mathematics 2018-11-22 Étienne Fouvry , Maksym Radziwiłł

An important result of H. Weyl states that for every sequence $\left(a_{n}\right)_{n\geq 1}$ of distinct positive integers the sequence of fractional parts of $\left(a_{n} \alpha \right)_{n \geq1}$ is uniformly distributed modulo one for…

Number Theory · Mathematics 2015-07-24 Christoph Aistleitner , Gerhard Larcher

For a probability measure $\mu$ on $[0,1]$ without discrete component, the best possible order of approximation by a finite point set in terms of the star-discrepancy is $\frac{1}{2N}$ as has been proven relatively recently. However, if…

Number Theory · Mathematics 2022-02-04 Christian Weiß

We focus on the problem estimating a monotone trend function under additive and dependent noise. New point-wise confidence interval estimators under both short- and long-range dependent errors are introduced and studied. These intervals are…

Statistics Theory · Mathematics 2016-02-23 Pramita Bagchi , Moulinath Banerjee , Stilian Stoev

We provide a sharp monotonicity theorem about the distribution of subharmonic functions on manifolds, which can be regarded as a new, measure theoretic form of the uncertainty principle. As an illustration of the scope of this result, we…

Classical Analysis and ODEs · Mathematics 2025-11-11 Aleksei Kulikov , Fabio Nicola , Joaquim Ortega-Cerdà , Paolo Tilli

The exponent of anomalous diffusion of virus in cytoplasm of a living cell is experimentally known to fluctuate depending on localized areas of the cytoplasm, indicating heterogeneity of diffusion. In a recent paper (Itto, 2012), a…

Biological Physics · Physics 2016-07-14 Yuichi Itto

We construct a variety of mappings of the unit interval into $\mathcal{L}^p([0,1])$ to generalize classical examples of $\mathcal{L}^p$-convergence of sequences of functions with simultaneous pointwise divergence. By establishing relations…

Classical Analysis and ODEs · Mathematics 2012-07-17 Vaios Laschos , Christian Mönch

Normal mixture distributions are arguably the most important mixture models, and also the most technically challenging. The likelihood function of the normal mixture model is unbounded based on a set of random samples, unless an artificial…

Statistics Theory · Mathematics 2009-08-25 Jiahua Chen , Pengfei Li