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We study random unrooted plane trees with $n$ vertices sampled according to the weights corresponding to the vertex-degrees. Our main result shows that if the generating series of the weights has positive radius of convergence, then this…

Probability · Mathematics 2018-09-17 Leon Ramzews , Benedikt Stufler

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 proposes an attributed network growth model. Despite the knowledge that individuals use limited resources to form connections to similar others, we lack an understanding of how local and resource-constrained mechanisms explain…

Social and Information Networks · Computer Science 2019-04-17 Harshay Shah , Suhansanu Kumar , Hari Sundaram

This paper studies higher index theory for a random sequence of bounded degree, finite graphs with diameter tending to infinity. We show that in a natural model for such random sequences the following hold almost surely: the coarse…

K-Theory and Homology · Mathematics 2014-04-28 Rufus Willett

Motivated by the problem of routing reliably and scalably in a graph, we introduce the notion of a splicer, the union of spanning trees of a graph. We prove that for any bounded-degree n-vertex graph, the union of two random spanning trees…

Discrete Mathematics · Computer Science 2008-07-10 Navin Goyal , Luis Rademacher , Santosh Vempala

Consider a graph with n nodes and m edges, independent edge weights and lengths, and arbitrary distance demands for node pairs. The spanner problem asks for a minimum-weight subgraph that satisfies these demands via sufficiently short paths…

Data Structures and Algorithms · Computer Science 2025-07-02 Fritz Bökler , Markus Chimani , Henning Jasper

In this paper we study the component structure of random graphs with independence between the edges. Under mild assumptions, we determine whether there is a giant component, and find its asymptotic size when it exists. We assume that the…

Probability · Mathematics 2010-06-29 Bela Bollobas , Svante Janson , Oliver Riordan

A paradigm that was successfully applied in the study of both pure and algorithmic problems in graph theory can be colloquially summarized as stating that "any graph is close to being the disjoint union of expanders". Our goal in this paper…

Combinatorics · Mathematics 2015-02-03 Guy Moshkovitz , Asaf Shapira

In this paper we construct spanning trees in hyperbolic graphs that represent their hyperbolic compactification in a good way: so that the tree has a bounded number of distinct rays to each boundary point. The bound depends only on the…

Combinatorics · Mathematics 2013-01-31 Matthias Hamann

A known failing of many popular random graph models is that the Aldous-Hoover Theorem guarantees these graphs are dense with probability one; that is, the number of edges grows quadratically with the number of nodes. This behavior is…

Statistics Theory · Mathematics 2016-03-23 Tamara Broderick , Diana Cai

The cactus of a pointed graph is a discrete tree associated with this graph. Similarly, with every pointed geodesic metric space $E$, one can associate an $\R$-tree called the continuous cactus of $E$. We prove under general assumptions…

Probability · Mathematics 2011-02-22 Nicolas Curien , Jean-François Le Gall , Grégory Miermont

In this last decade, an important stochastic model emerged: the Brownian map. It is the limit of various models of random combinatorial maps after rescaling: it is a random metric space with Hausdorff dimension 4, almost surely homeomorphic…

Probability · Mathematics 2020-01-22 Luca Lionni , Jean-François Marckert

We use a natural ordered extension of the Chinese Restaurant Process to grow a two-parameter family of binary self-similar continuum fragmentation trees. We provide an explicit embedding of Ford's sequence of alpha model trees in the…

Probability · Mathematics 2009-09-25 Jim Pitman , Matthias Winkel

For non-negative integers $(d_n(k))_{k \ge 1}$ such that $\sum_{k \ge 1} d_n(k) = n$, we sample a bipartite planar map with $n$ faces uniformly at random amongst those which have $d_n(k)$ faces of degree $2k$ for every $k \ge 1$ and we…

Probability · Mathematics 2020-07-20 Cyril Marzouk

The random graph model has recently been extended to a random preferential attachment graph model, in order to enable the study of general asymptotic properties in network types that are better represented by the preferential attachment…

Social and Information Networks · Computer Science 2015-02-10 Chen Avin , Zvi Lotker , David Peleg

Desirable random graph models (RGMs) should (i) reproduce common patterns in real-world graphs (e.g., power-law degrees, small diameters, and high clustering), (ii) generate variable (i.e., not overly similar) graphs, and (iii) remain…

Machine Learning · Computer Science 2025-09-26 Fanchen Bu , Ruochen Yang , Paul Bogdan , Kijung Shin

We study the preferential attachment model $G_n^h$. A graph $G_n^h$ is generated from a finite initial graph by adding new vertices one at a time. Each new vertex connects to $h\ge 1$ already existing vertices, and these are chosen with…

Probability · Mathematics 2026-01-12 Katarzyna Rybarczyk , Małgorzata Sulkowska

We study random bipartite planar maps defined by assigning nonnegative weights to each face of a map. We prove that for certain choices of weights a unique large face, having degree proportional to the total number of edges in the maps,…

Probability · Mathematics 2015-06-05 Svante Janson , Sigurdur Örn Stefánsson

The term "strong approximation" is used to describe phenomena where an arithmetic group as well as all of its Zariski dense subgroups have a large image in the congruence quotients. We exhibit analogues of such phenomena in a probabilistic,…

Combinatorics · Mathematics 2009-05-05 Yair Glasner

We study the problem of learning a latent tree graphical model where samples are available only from a subset of variables. We propose two consistent and computationally efficient algorithms for learning minimal latent trees, that is, trees…

Machine Learning · Statistics 2010-09-15 Myung Jin Choi , Vincent Y. F. Tan , Animashree Anandkumar , Alan S. Willsky