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Estimating a large alphabet probability distribution from a limited number of samples is a fundamental problem in machine learning and statistics. A variety of estimation schemes have been proposed over the years, mostly inspired by the…

Machine Learning · Statistics 2018-08-20 Amichai Painsky , Meir Feder

We consider systems of stochastic fixed-point equations that arise in the asymptotic analysis of random recursive structures and algorithms such as Quicksort, generalized P\'olya urn processes and path lengths of random recursive trees and…

Probability · Mathematics 2018-03-08 Kevin Leckey

In this article, we study the pointwise asymptotic behavior of iterated convolutions on the one dimensional lattice Z. We generalize the so-called local limit theorem in probability theory to complex valued sequences. A sharp rate of…

Probability · Mathematics 2025-02-25 Lucas Coeuret

We establish some limit theorems for quasi-arithmetic means of random variables. This class of means contains the arithmetic, geometric and harmonic means. Our feature is that the generators of quasi-arithmetic means are allowed to be…

Statistics Theory · Mathematics 2022-05-09 Yuichi Akaoka , Kazuki Okamura , Yoshiki Otobe

We study a generalised model of population growth in which the state variable is population growth rate instead of population size. Stochastic parametric perturbations, modelling phenotypic variability, lead to a Langevin system with two…

Populations and Evolution · Quantitative Biology 2010-10-15 Harold P. de Vladar , Ido Pen

We derive a Gaussian Central Limit Theorem for the sample quantiles based on locally dependent random variables with explicit convergence rate. Our approach is based on converting the problem to a sum of indicator random variables, applying…

Probability · Mathematics 2025-03-05 Partha S. Dey , Grigory Terlov

Recently, the first author showed that the giant in random undirected graphs is `almost' local. This means that, under a necessary and sufficient condition, the limiting proportion of vertices in the giant converges in probability to the…

Probability · Mathematics 2025-07-24 Remco van der Hofstad , Manish Pandey

For normalized sums $Z_n$ of i.i.d. random variables, we explore necessary and sufficient conditions which guarantee the normal approximation with respect to the R\'enyi divergence of infinite order. In terms of densities $p_n$ of $Z_n$,…

Probability · Mathematics 2024-06-21 Sergey G. Bobkov , Friedrich Götze

We present some product representations for random variables with the Linnik, Mittag-Leffler and Weibull distributions and establish the relationship between the mixing distributions in these representations. Based on these representations,…

Probability · Mathematics 2016-02-09 V. Yu. Korolev , A. I. Zeifman

We study measures on random partitions, arising from condensing stochastic particle systems with stationary product distributions. We provide fairly general conditions on the stationary weights, which lead to Poisson-Dirichlet statistics of…

Probability · Mathematics 2023-03-06 Paul Chleboun , Simon Gabriel , Stefan Grosskinsky

We consider a string with fixed endpoints where the mass density and/or the elastic coefficient vary in a self-affine way as function of position. It is demonstrated how the eigenvalues in the asymptotic limit are distributed. Scaling laws…

Disordered Systems and Neural Networks · Physics 2007-05-23 Ingve Simonsen , Alex Hansen

We consider self-loops and multiple edges in the configuration model as the size of the graph tends to infinity. The interest in these random variables is due to the fact that the configuration model, conditioned on being simple, is a…

Probability · Mathematics 2017-02-06 Omer Angel , Remco van der Hofstad , Cecilia Holmgren

We propose an alternate approach to quantifying how well language models learn natural language: we ask how well they match the statistical tendencies of natural language. To answer this question, we analyze whether text generated from…

Computation and Language · Computer Science 2021-08-31 Clara Meister , Ryan Cotterell

Population protocols are a model of distributed computing, in which $n$ agents with limited local state interact randomly, and cooperate to collectively compute global predicates. An extensive series of papers, across different communities,…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-07-17 Dan Alistarh , James Aspnes , Rati Gelashvili

Limiting distributions are derived for the sparse connected components that are present when a random graph on $n$ vertices has approximately $\half n$ edges. In particular, we show that such a graph consists entirely of trees, unicyclic…

Probability · Mathematics 2008-02-03 Svante Janson , Donald E. Knuth , Tomasz Łuczak , Boris Pittel

Consider generalized adapted stochastic integrals with respect to independently scattered random measures with second moments. We use a decoupling technique, known as the "principle of conditioning", to study their stable convergence…

Probability · Mathematics 2007-05-23 Giovanni Peccati , Murad S. Taqqu

Li and Wu proposed Rule 2, a localized approximation algorithm that attempts to find a small connected dominating set in a graph. Here we study the asymptotic performance of Rule 2 on random unit disk graphs formed from n random points in…

Discrete Mathematics · Computer Science 2007-05-23 Jennie C. Hansen , Eric Schmutz , Li Sheng

We study rank-frequency relations for phonemes, the minimal units that still relate to linguistic meaning. We show that these relations can be described by the Dirichlet distribution, a direct analogue of the ideal-gas model in statistical…

Computation and Language · Computer Science 2016-04-22 Weibing Deng , Armen E. Allahverdyan

We generalise the Erdos-Renyi limit theorem on the maximum of the partial sums of random variables to the case when the number of terms in these sums is randomly distributed. Certain relations between the limiting theorems of this type and…

Probability · Mathematics 2007-05-23 A. Khorunzhy

For a uniform random labelled tree, we find the limiting distribution of tree parameters which are stable (in some sense) with respect to local perturbations of the tree structure. The proof is based on the martingale central limit theorem…

Combinatorics · Mathematics 2022-06-16 Mikhail Isaev , Angus Southwell , Maksim Zhukovskii