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Consider a rooted infinite Galton-Watson tree with mean offspring number $m>1$, and a collection of i.i.d. positive random variables $\xi_e$ indexed by all the edges in the tree. We assign the resistance $m^d \xi_e$ to each edge $e$ at…

Probability · Mathematics 2018-05-21 Dayue Chen , Yueyun Hu , Shen Lin

Consider the d-dimensional lattice Z^d where each vertex is ``open'' or ``closed'' with probability p or 1-p, respectively. An open vertex v is connected by an edge to the closest open vertex w such that the dth co-ordinates of v and w…

Probability · Mathematics 2016-09-07 Sreela Gangopadhyay , Rahul Roy , Anish Sarkar

Random forests is a state-of-the-art supervised machine learning method which behaves well in high-dimensional settings although some limitations may happen when $p$, the number of predictors, is much larger than the number of observations…

Methodology · Statistics 2019-02-01 Louis Capitaine , Robin Genuer , Rodolphe Thiébaut

The study of patterns in permutations associated with forests of binary shrubs was initiated by D. Bevan et al.. In this paper, we study five different types of rise statistics that can be associated with such permutations and find the…

Combinatorics · Mathematics 2023-06-22 Jeffrey Remmel , Sai-nan Zheng

Inspired by [4] we present a new algorithm for uniformly random generation of ordered trees in which all occuring outdegrees can be specified by a given sequence of numbers. The method can be used for random generation of binary or n-ary…

Discrete Mathematics · Computer Science 2021-12-30 Aleksander Kiryk

We introduce the notion of a hereditary property for rooted real trees and we also consider reduction of trees by a given hereditary property. Leaf-length erasure, also called trimming, is included as a special case of hereditary reduction.…

Probability · Mathematics 2012-11-12 Thomas Duquesne , Matthias Winkel

Galled trees are studied as a recombination model in theoretic population genetics. This class of phylogenetic networks has been generalized to tree-child networks, normal networks and tree-based networks by relaxing a structural condition.…

Populations and Evolution · Quantitative Biology 2019-08-05 Louxin Zhang

We consider a Gibbs distribution over all spanning trees of an undirected, edge weighted finite graph, where, up to normalization, the probability of each tree is given by the product of its edge weights. Defining the weighted degree of a…

Discrete Mathematics · Computer Science 2024-10-18 Enrique Fita Sanmartín , Christoph Schnörr , Fred A. Hamprecht

P\'olya trees are rooted trees considered up to symmetry. We establish the convergence of large uniform random P\'olya trees with arbitrary degree restrictions to Aldous' Continuum Random Tree with respect to the Gromov-Hausdorff metric.…

Probability · Mathematics 2016-12-12 Konstantinos Panagiotou , Benedikt Stufler

We consider the process of uncovering the vertices of a random labeled tree according to their labels. First, a labeled tree with $n$ vertices is generated uniformly at random. Thereafter, the vertices are uncovered one by one, in order of…

Probability · Mathematics 2023-01-03 Benjamin Hackl , Alois Panholzer , Stephan Wagner

Data analysis and machine learning have become an integrative part of the modern scientific methodology, offering automated procedures for the prediction of a phenomenon based on past observations, unraveling underlying patterns in data and…

Machine Learning · Statistics 2015-06-04 Gilles Louppe

A tree is scattered if no subdivision of the complete binary tree is a subtree. Building on results of Halin, Polat and Sabidussi, we identify four types of subtrees of a scattered tree and a function of the tree into the integers at least…

Combinatorics · Mathematics 2016-10-03 Claude Laflamme , Maurice Pouzet , Norbert Sauer

In frozen percolation, i.i.d. uniformly distributed activation times are assigned to the edges of a graph. At its assigned time, an edge opens provided neither of its endvertices is part of an infinite open cluster; in the opposite case, it…

Probability · Mathematics 2020-12-03 Balázs Ráth , Jan M. Swart , Tamás Terpai

We introduce and study a model of plane random trees generalizing the famous Bienaym\'e--Galton--Watson model but where births and deaths are locally correlated. More precisely, given a random variable $(B,H)$ with values in $\{1,2,3,…

Probability · Mathematics 2025-11-21 Ariane Carrance , Jérôme Casse , Nicolas Curien

We extend classical results on simple varieties of trees (asymptotic enumeration, average behavior of tree parameters) to trees counted by their number of leaves. Motivated by genome comparison of related species, we then apply these…

Combinatorics · Mathematics 2016-10-03 Mathilde Bouvel , Marni Mishna , Cyril Nicaud

Binary rooted trees, both in the ordered and in the un-ordered case, are well studied structures in the field of combinatorics. The aim of this work is to study particular patterns in these classes of trees. We consider completely…

Combinatorics · Mathematics 2013-03-12 Filippo Disanto

Rooted, weighted continuum random trees are used to describe limits of sequences of random discrete trees. Formally, they are random quadruples $(\mathcal{T},d,r,p)$, where $(\mathcal{T},d)$ is a tree-like metric space, $r\in\mathcal{T}$ is…

Probability · Mathematics 2021-01-29 Noah Forman

Random forests are a scheme proposed by Leo Breiman in the 2000's for building a predictor ensemble with a set of decision trees that grow in randomly selected subspaces of data. Despite growing interest and practical use, there has been…

Machine Learning · Statistics 2012-03-28 Gérard Biau

Phylogenetic networks generalise phylogenetic trees and allow for the accurate representation of the evolutionary history of a set of present-day species whose past includes reticulate events such as hybridisation and lateral gene transfer.…

Populations and Evolution · Quantitative Biology 2018-09-05 Joan Carles Pons , Charles Semple , Mike Steel

Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As suggested by Breiman, the strength of unstable learners and the diversity among them are the ensemble models' core strength. In this paper,…

Machine Learning · Computer Science 2022-08-11 M. A. Ganaie , M. Tanveer , P. N. Suganthan , V. Snasel