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In this work, we consider the sample complexity required for testing the monotonicity of distributions over partial orders. A distribution $p$ over a poset is monotone if, for any pair of domain elements $x$ and $y$ such that $x \preceq y$,…

Data Structures and Algorithms · Computer Science 2019-07-09 Maryam Aliakbarpour , Themis Gouleakis , John Peebles , Ronitt Rubinfeld , Anak Yodpinyanee

Suppose an interval is put on a horizontal line with random roughness. With probability one it is supported at two points, one from the left, and another from the right from its center. We compute probability distribution of support points…

Probability · Mathematics 2013-05-20 Dmitry Treschev

We start by reviewing recent probabilistic results on ergodic sums in a large class of (non-uniformly) hyperbolic dynamical systems. Namely, we describe the central limit theorem, the almost-sure convergence to the gaussian and other stable…

Dynamical Systems · Mathematics 2012-05-09 J. -R. Chazottes

Bi-capacities arise as a natural generalization of capacities (or fuzzy measures) in a context of decision making where underlying scales are bipolar. They are able to capture a wide variety of decision behaviours, encompassing models such…

Discrete Mathematics · Computer Science 2007-11-15 Michel Grabisch , Christophe Labreuche

We consider simple exclusion processes on Z for which the underlying random walk has a finite first moment and a non-zero mean and whose initial distributions are product measures with different densities to the left and to the right of the…

Probability · Mathematics 2011-11-10 E. Andjel , P. A. Ferrari , A. Siqueira

The empirical measure of an interacting particle system is a purely atomic random probability measure. In the limit as the number of particles grows to infinity, we show for McKean-Vlasov systems with common noise that this measure becomes…

Probability · Mathematics 2025-09-01 Robert Alexander Crowell

We study large partial sums, localized with respect to the sums of variances, of a sequence of centered random variables. An application is given to the distribution of prime factors of typical integers.

Probability · Mathematics 2007-11-21 Kevin Ford , Gerald Tenenbaum

We study the scaling limit of the capacity of the range of a simple random walk on the integer lattice in dimension four. We establish a strong law of large numbers and a central limit theorem with a non-gaussian limit. The asymptotic…

Probability · Mathematics 2016-12-30 Amine Asselah , Bruno Schapira , Perla Sousi

Spaces with locally varying scale of measurement, like multidimensional structures with differently scaled dimensions, are pretty common in statistics and machine learning. Nevertheless, it is still understood as an open question how to…

Machine Learning · Statistics 2024-03-05 Christoph Jansen , Georg Schollmeyer , Hannah Blocher , Julian Rodemann , Thomas Augustin

We consider inequalities where integrals are defined in the sense of Choquet with respect to Hausdorff content. We study cases where continuously differentiable functions are defined on open, connected sets with so much regularity that…

Functional Analysis · Mathematics 2023-11-27 Petteri Harjulehto , Ritva Hurri-Syrjänen

The study of the distribution of volumes associated to the internal representations of learning examples allows us to derive the critical learning capacity ($\alpha_c=\frac{16}{\pi} \sqrt{\ln K}$) of large committee machines, to verify the…

Condensed Matter · Physics 2007-05-23 Remi Monasson , Riccardo Zecchina

In a statistical cluster or loop model such as percolation, or more generally the Potts models or O(n) models, a pinch point is a single bulk point where several distinct clusters or loops touch. In a polygon P harboring such a model in its…

Mathematical Physics · Physics 2015-06-04 Steven M. Flores , Peter Kleban , Robert M. Ziff

In many applications, data cluster. Failing to take the cluster structure into consideration generally leads to underestimated variances of point estimators and inflated type I errors in hypothesis tests. Many circumstance-dependent…

Methodology · Statistics 2025-07-21 Jiahua Chen , Pengfei Li , Yukun Liu , James V. Zidek

We introduce the aggregated clustering problem, where one is given $T$ instances of a center-based clustering task over the same $n$ points, but under different metrics. The goal is to open $k$ centers to minimize an aggregate of the…

Data Structures and Algorithms · Computer Science 2025-10-10 Deeparnab Chakrabarty , Jonathan Conroy , Ankita Sarkar

The set of short intervals between consecutive primes squared has the pleasant---but seemingly unexploited---property that each interval $s_k:=\{p_k^2, \dots,p_{k+1}^2-1\}$ is fully sieved by the $k$ first primes. Here we take advantage of…

Number Theory · Mathematics 2014-08-13 Kolbjørn Tunstrøm

We revisit the problem of condensation for independent, identically distributed random variables with a power-law tail, conditioned by the value of their sum. For large values of the sum, and for a large number of summands, a condensation…

Statistical Mechanics · Physics 2022-03-03 Claude Godrèche

A continuous map $f$ from a compact interval $I$ into itself is densely (resp. generically) chaotic if the set of points $(x,y)$ such that $\limsup_{n\to+\infty}|f^n(x)-f^n(y)|>0$ and $\liminf_{n\to+\infty} |f^n(x)-f^n(y)|=0$ is dense…

Dynamical Systems · Mathematics 2019-01-09 Sylvie Ruette

Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients, and weakly dependent errors, are considered for observations over time, space or space--time. Consistency and asymptotic normality of…

Statistics Theory · Mathematics 2012-05-14 Peter M. Robinson

The law of large numbers is one of the fundamental properties which algorithmically random infinite sequences ought to satisfy. In this paper, we show that the law of large numbers can be effectivized for an arbitrary Schnorr random…

Probability · Mathematics 2022-12-29 Kohtaro Tadaki

Let $X_1,X_2, \ldots $ be independent random uniform points in a bounded domain $A \subset \mathbb{R}^d$ with smooth boundary. Define the coverage threshold $R_n$ to be the smallest $r$ such that $A$ is covered by the balls of radius $r$…

Probability · Mathematics 2022-01-12 Mathew D. Penrose