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We investigate the behaviour of five classical centrality measures--Jordan, rumor, betweenness, degree, and closeness centralities--in the setting of uniform random recursive trees. Motivated by applications in network archaeology, we focus…

Probability · Mathematics 2026-03-23 Richard Coll Josifov , Luc Devroye , Gabor Lugosi

We introduce a random graph model based on k-trees, which can be generated by applying a probabilistic preferential attachment rule, but which also has a simple combinatorial description. We carry out a precise distributional analysis of…

Combinatorics · Mathematics 2010-03-02 Alois Panholzer , Georg Seitz

We study the influence of the seed in random trees grown according to the uniform attachment model, also known as uniform random recursive trees. We show that different seeds lead to different distributions of limiting trees from a total…

Probability · Mathematics 2014-10-22 Sébastien Bubeck , Ronen Eldan , Elchanan Mossel , Miklós Z. Rácz

We consider models of growing random trees $\{\mathcal{T}_f(n):n\geq 1\}$ with model dynamics driven by an attachment function $f:\mathbb{Z}_+\to \mathbb{R}_+$. At each stage a new vertex enters the system and connects to a vertex $v$ in…

Probability · Mathematics 2021-08-11 Sayan Banerjee , Shankar Bhamidi

We study two models of growing recursive trees. For both models, initially the tree only contains one vertex $u_1$ and at each time $n\geq 2$ a new vertex $u_n$ is added to the tree and its parent is chosen randomly according to some rule.…

Probability · Mathematics 2020-06-04 Delphin Sénizergues

We study a random recursive tree model featuring complete redirection called the random friend tree and introduced by Saram\"aki and Kaski. Vertices are attached in a sequential manner one by one by selecting an existing target vertex and…

The recursive and hierarchical structure of full rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. In most of these cases, the full rooted tree is…

Machine Learning · Statistics 2022-03-24 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

We investigate centrality and root-inference properties in a class of growing random graphs known as sublinear preferential attachment trees. We show that a continuous time branching processes called the Crump-Mode-Jagers (CMJ) branching…

Probability · Mathematics 2016-10-28 Varun Jog , Po-Ling Loh

We investigate properties of node centrality in random growing tree models. We focus on a measure of centrality that computes the maximum subtree size of the tree rooted at each node, with the most central node being the tree centroid. For…

Probability · Mathematics 2015-11-09 Varun Jog , Po-Ling Loh

In the broadcasting problem on trees, a $\{-1,1\}$-message originating in an unknown node is passed along the tree with a certain error probability $q$. The goal is to estimate the original message without knowing the order in which the…

Probability · Mathematics 2025-09-12 Ernst Althaus , Lisa Hartung , Rebecca Steiner

The reconstruction of large phylogenetic trees from data that violates clocklike evolution (or as a supertree constructed from any m input trees) raises a difficult question for biologists - how can one assign relative dates to the vertices…

Combinatorics · Mathematics 2007-05-23 Tanja Gernhard , Daniel Ford , Rutger Vos , Mike Steel

The purpose of this paper is to analyze certain statistics of a recently introduced non-uniform random tree model, biased recursive trees. This model is based on constructing a random tree by establishing a correspondence with non-uniform…

Probability · Mathematics 2018-01-16 Ella Hiesmayr , Ümit Işlak

We show that an algorithmic construction of sequences of recursive trees leads to a direct proof of the convergence of random recursive trees in an associated Doob-Martin compactification; it also gives a representation of the limit in…

Probability · Mathematics 2014-07-01 Rudolf Grübel , Igor Michailow

This paper studies the problem of recursively estimating the weighted adjacency matrix of a network out of a temporal sequence of binary-valued observations. The observation sequence is generated from nonlinear networked dynamics in which…

Systems and Control · Electrical Eng. & Systems 2019-12-06 Yu Xing , Xingkang He , Haitao Fang , Karl Henrik Johansson

Several real-world and abstract structures and systems are characterized by marked hierarchy to the point of being expressed as trees. Because the study of these entities often involves sampling (or discovering) the tree nodes in a specific…

Physics and Society · Physics 2022-04-18 Alexandre Benatti , Luciano da F. Costa

A weighted recursive tree is an evolving tree in which vertices are assigned random vertex-weights and new vertices connect to a predecessor with a probability proportional to its weight. Here, we study the maximum degree and near-maximum…

Probability · Mathematics 2023-01-31 Laura Eslava , Bas Lodewijks , Marcel Ortgiese

We propose a randomized a posteriori error estimator for reduced order approximations of parametrized (partial) differential equations. The error estimator has several important properties: the effectivity is close to unity with prescribed…

Numerical Analysis · Mathematics 2019-04-02 Kathrin Smetana , Olivier Zahm , Anthony T Patera

We consider linear preferential attachment trees, and show that they can be regarded as random split trees in the sense of Devroye (1999), although with infinite potential branching. In particular, this applies to the random recursive tree…

Probability · Mathematics 2017-06-20 Svante Janson

Random spanning trees are among the most prominent determinantal point processes. We give four examples of random spanning trees on ladder-like graphs whose rungs form stationary renewal processes or regenerative processes of order two,…

Probability · Mathematics 2017-04-04 Achim Klenke

Assume we are given a set of items from a general metric space, but we neither have access to the representation of the data nor to the distances between data points. Instead, suppose that we can actively choose a triplet of items (A,B,C)…

Machine Learning · Statistics 2018-06-19 Siavash Haghiri , Damien Garreau , Ulrike von Luxburg
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