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Phylogenetic networks generalize phylogenetic trees by allowing the modelization of events of reticulate evolution. Among the different kinds of phylogenetic networks that have been proposed in the literature, the subclass of binary…

Data Structures and Algorithms · Computer Science 2020-07-01 Gabriel Cardona , Joan Carles Pons , Celine Scornavacca

A general formulation is presented for continuum scaling limits of stochastic spanning trees. A spanning tree is expressed in this limit through a consistent collection of subtrees, which includes a tree for every finite set of endpoints in…

Probability · Mathematics 2012-06-19 Michael Aizenman , Almut Burchard , Charles M. Newman , David B. Wilson

We consider the random walk attachment graph introduced by Saram\"{a}ki and Kaski and proposed as a mechanism to explain how behaviour similar to preferential attachment may appear requiring only local knowledge. We show that if the length…

Probability · Mathematics 2013-07-24 Chris Cannings , Jonathan Jordan

Consider a generalised preferential attachment tree with attachment function $f$, that is a random tree, where at each time-step a node connects to an existing node $v$ with probability proportional to $f(\mathrm{deg}(v))$, where…

Probability · Mathematics 2026-04-17 Tejas Iyer

A fringe subtree of a rooted tree is a subtree consisting of one of the nodes and all its descendants. In this paper, we are specifically interested in the number of non-isomorphic trees that appear in the collection of all fringe subtrees…

Combinatorics · Mathematics 2020-03-09 Louisa Seelbach Benkner , Stephan Wagner

We introduce a collection of complex networks generated by a combination of preferential attachment and a previously unexamined process of "splitting" nodes of degree $k$ into $k$ nodes of degree 1. Four networks are considered, each…

Physics and Society · Physics 2013-09-25 E. R. Colman , G. J. Rodgers

We introduce a novel interpretable tree based algorithm for prediction in a regression setting. Our motivation is to estimate the unknown regression function from a functional decomposition perspective in which the functional components…

Machine Learning · Statistics 2023-08-04 Munir Hiabu , Enno Mammen , Joseph T. Meyer

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 study fragmentation of a random recursive tree into a forest by repeated removal of nodes. The initial tree consists of N nodes and it is generated by sequential addition of nodes with each new node attaching to a randomly-selected…

Statistical Mechanics · Physics 2014-12-25 Z. Kalay , E. Ben-Naim

One of the main virtues of trees is to represent formal solutions of various functional equations which can be cast in the form of fixed point problems. Basic examples include differential equations and functional (Lagrange) inversion in…

Combinatorics · Mathematics 2013-02-12 Florent Hivert , Jean-Christophe Novelli , Jean-Yves Thibon

We study randomly growing trees governed by the affine preferential attachment rule. Starting with a seed tree $S$, vertices are attached one by one, each linked by an edge to a random vertex of the current tree, chosen with a probability…

Probability · Mathematics 2018-11-01 David Corlin Marchand , Ioan Manolescu

Preferential attachment graphs are random graphs designed to mimic properties of typical real world networks. They are constructed by a random process that iteratively adds vertices and attaches them preferentially to vertices that already…

Discrete Mathematics · Computer Science 2018-03-30 Jan Dreier , Philipp Kuinke , Peter Rossmanith

Motivated by the properties of the descent polynomials, which enumerate permutations of $S_n$ with a fixed descent set, we define descent polynomials for labeled rooted trees. We give recursive and explicit formulas for these polynomials…

Combinatorics · Mathematics 2023-05-02 Svetlana Poznanović , Maria Rodriguez Hertz , Solomon Valore-Caplan , David Wichmann

Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of…

It has been claimed in Aldous, Miermont and Pitman [PTRF, 2004] that all L\'evy trees are mixings of inhomogeneous continuum random trees. We give a rigorous proof of this claim in the case of a stable branching mechanism, relying on a new…

Probability · Mathematics 2022-11-15 Minmin Wang

We propose a new arithmetic for non-empty rooted unordered trees simply called trees. After discussing tree representation and enumeration, we define the operations of tree addition, multiplication and stretch, prove their properties, and…

Discrete Mathematics · Computer Science 2016-02-02 Fabrizio Luccio

Random forests are widely used in regression. However, the decision trees used as base learners are poor approximators of linear relationships. To address this limitation we propose RaFFLE (Random Forest Featuring Linear Extensions), a…

Machine Learning · Computer Science 2025-02-17 Jakob Raymaekers , Peter J. Rousseeuw , Thomas Servotte , Tim Verdonck , Ruicong Yao

Random increasing k-trees represent an interesting, useful class of strongly dependent graphs for which analytic-combinatorial tools can be successfully applied. We study in this paper a notion called connectivity-profile and derive…

Combinatorics · Mathematics 2009-10-20 Alexis Darrasse , Hsien-Kuei Hwang , Olivier Bodini , Michèle Soria

We present here a new and universal approach for the study of random and/or trees, unifying in one framework many different models, including some novel ones not yet understood in the literature. An and/or tree is a Boolean expression…

Probability · Mathematics 2017-06-09 Nicolas Broutin , Cécile Mailler

Random Forests are one of the most popular classifiers in machine learning. The larger they are, the more precise is the outcome of their predictions. However, this comes at a cost: their running time for classification grows linearly with…

Machine Learning · Computer Science 2019-12-24 Frederik Gossen , Bernhard Steffen