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We study a generalized P\'{o}lya urn model with two types of ball. If the drawn ball is red, it is replaced together with a black ball, but if the drawn ball is black it is replaced and a red ball is thrown out of the urn. When only black…

Probability · Mathematics 2012-01-17 Edward Crane , Nicholas Georgiou , Stanislav Volkov , Andrew R. Wade , Robert J. Waters

Generalized Friedman urn is one of the simplest and most useful models considered in probability theory. Since Athreya and Ney (1972) showed the almost sure convergence of urn proportions in a randomized urn model with irreducible…

Probability · Mathematics 2022-04-12 Li-Xin Zhang

Consider two urns, $A$ and $B$, where initially $A$ contains a large number $n$ of balls and $B$ is empty. At each step, with equal probability, either we pick a ball at random in $A$ and place it in $B$, or vice-versa (provided of course…

Probability · Mathematics 2010-07-26 Jean Bertoin

In this work we discuss two urn models with general weight sequences $(A,B)$ associated to them, $A=(\alpha_n)_{n\in\N}$ and $B=(\beta_m)_{m\in\N}$, generalizing two well known P\'olya-Eggenberger urn models, namely the so-called sampling…

Combinatorics · Mathematics 2010-05-11 Markus Kuba

We study the joint asymptotics of forward and backward processes of numbers of non-empty urns in an infinite urn scheme. The probabilities of balls hitting the urns are assumed to satisfy the conditions of regular decrease. We prove weak…

Probability · Mathematics 2022-11-10 Mikhail Chebunin , Artyom Kovalevskii

Stochastic approximation algorithm is a useful technique which has been exploited successfully in probability theory and statistics for a long time. The step sizes used in stochastic approximation are generally taken to be deterministic and…

Probability · Mathematics 2019-09-25 Ujan Gangopadhyay , Krishanu Maulik

We consider systems of interacting Generalized Friedman's Urns (GFUs) having irreducible mean replacement matrices. The interaction is modeled through the probability to sample the colors from each urn, that is defined as convex combination…

Probability · Mathematics 2018-01-09 Giacomo Aletti , Andrea Ghiglietti

This paper introduces and analyzes a particular class of Polya urns: balls are of two colors, can only be added (the urns are said to be additive) and at every step the same constant number of balls is added, thus only the color…

Combinatorics · Mathematics 2012-03-26 Basile Morcrette

An urn model of Diaconis and some generalizations are discussed. A convergence theorem is proved that implies for Diaconis' model that the empirical distribution of balls in the urn converges with probability one to the uniform…

Probability · Mathematics 2007-05-23 David Siegmund , Benjamin Yakir

We consider a generalized two-color Polya urn (black and withe balls) first introduced by Hill, Lane, Sudderth where the urn composition evolves as follows: let $\pi:\left[0,1\right]\rightarrow\left[0,1\right]$, and denote by $x_{n}$ the…

Probability · Mathematics 2025-07-09 Simone Franchini

In this paper, we present a brief survey of Reinforcement Learning (RL), with particular emphasis on Stochastic Approximation (SA) as a unifying theme. The scope of the paper includes Markov Reward Processes, Markov Decision Processes,…

Machine Learning · Computer Science 2023-04-04 Mathukumalli Vidyasagar

We answer Problem 11.1 of Janson arXiv:1803.04207 on P\'olya urns associated with stable random walk. Our proof use neither martingales nor trees, but an approximation with a differential equation.

Probability · Mathematics 2024-02-13 Arthur Blanc-Renaudie

There have been key advancements to building universal approximators for multi-goal collections of reinforcement learning value functions -- key elements in estimating long-term returns of states in a parameterized manner. We extend this to…

Machine Learning · Computer Science 2024-10-29 Rushiv Arora

This paper provides a unifying view of a wide range of problems of interest in machine learning by framing them as the minimization of functionals defined on the space of probability measures. In particular, we show that generative…

Machine Learning · Computer Science 2019-05-21 Casey Chu , Jose Blanchet , Peter Glynn

We prove a central limit theorem applicable to one dimensional stochastic approximation algorithms that converge to a point where the error terms of the algorithm do not vanish. We show how this applies to a certain class of these…

Probability · Mathematics 2011-02-24 Henrik Renlund

We consider the generalization of the P\'olya urn scheme with possibly infinite many colors as introduced in \cite{Th-Thesis, BaTH2014, BaTh2016, BaTh2017}. For countable many colors, we prove almost sure convergence of the urn…

Probability · Mathematics 2021-06-08 Antar Bandyopadhyay , Svante Janson , Debleena Thacker

We show that the supremum of the successive percentages of red balls in P\'olya's urn model is almost surely rational, give the set of values that are taken with positive probability and derive several exact distributional results for the…

Probability · Mathematics 2014-10-10 Ernst Schulte-Geers , Wolfgang Stadje

Generalized Polya urn models have been used to model the establishment dynamics of a small founding population consisting of k different genotypes or strategies. As population sizes get large, these population processes are…

Probability · Mathematics 2016-11-04 Mathieu Faure , Sebastian Schreiber

This paper presents new uniform Gaussian strong approximations for empirical processes indexed by classes of functions based on $d$-variate random vectors ($d\geq1$). First, a uniform Gaussian strong approximation is established for general…

Statistics Theory · Mathematics 2024-11-14 Matias D. Cattaneo , Ruiqi Rae Yu

In this paper, we consider a multi-drawing urn model with random addition. At each discrete time step, we draw a sample of m balls. According to the composition of the drawn colors, we return the balls together with a random number of balls…

Probability · Mathematics 2018-02-14 Rafik Aguech , Nabil Lasmar , Olfa Selmi
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