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Building upon the theory of graph limits and the Aldous-Hoover representation and inspired by Panchenko's work on asymptotic Gibbs measures (Annals of Probability 2013), we construct continuous embeddings of discrete probability…

Probability · Mathematics 2017-11-17 Amin Coja-Oghlan , Will Perkins , Kathrin Skubch

Let G be an edge-weighted hypergraph on n vertices, m edges of size \le s, where the edges have real weights in an interval [1,W]. We show that if we can approximate a maximum weight matching in G within factor alpha in time T(n,m,W) then…

Data Structures and Algorithms · Computer Science 2011-01-12 Andrzej Lingas , Cui Di

We review mathematically tractable models for connected networks on random points in the plane, emphasizing the class of proximity graphs which deserves to be better known to applied probabilists and statisticians. We introduce and motivate…

Probability · Mathematics 2011-01-06 David J. Aldous , Julian Shun

Let P_{n,d,D} denote the graph taken uniformly at random from the set of all labelled planar graphs on {1,2,...,n} with minimum degree at least d(n) and maximum degree at most D(n). We use counting arguments to investigate the probability…

Combinatorics · Mathematics 2011-01-28 Chris Dowden

Many real-world networks exhibit the so-called small-world phenomenon: their typical distances are much smaller than their sizes. One mathematical model for this phenomenon is a long-range percolation graph on a $d$-dimensional box $\{0, 1,…

Probability · Mathematics 2022-11-30 Tianqi Wu

We study the joint degree counts in proportional attachment random graphs and find a simple representation for the limit distribution in infinite sequence space. We show weak convergence with respect to the p-norm topology for appropriate p…

Probability · Mathematics 2016-12-09 Erol A. Peköz , Adrian Röllin , Nathan Ross

We prove that for any unweighted graph on n vertices the L1 norm of a unit electric current between the endpoints of a random edge is at most 2 log n. Furthermore, we show that on any weighted graph the spectral norm of the entry-wise…

Data Structures and Algorithms · Computer Science 2026-05-26 Ori Gurel-Gurevich , Asaf Nachmias , Sushant Sachdeva

Consider a graph on $n$ uniform random points in the unit square, each pair being connected by an edge with probability $p$ if the inter-point distance is at most $r$. We show that as $n\to\infty$ the probability of full connectivity is…

Probability · Mathematics 2016-04-07 Mathew D. Penrose

Consider the continuum of points along the edges of a network, i.e., a connected, undirected graph with positive edge weights. We measure the distance between these points in terms of the weighted shortest path distance, called the network…

Data Structures and Algorithms · Computer Science 2015-07-30 Carsten Grimm

In this paper we study the impact of random exponential edge weights on the distances in a random graph and, in particular, on its diameter. Our main result consists of a precise asymptotic expression for the maximal weight of the shortest…

Probability · Mathematics 2015-04-17 Hamed Amini , Marc Lelarge

For random combinatorial optimization problems, there has been much progress in establishing laws of large numbers and computing limiting constants for the optimal value of various problems. However, there has not been as much success in…

Probability · Mathematics 2020-08-24 Sky Cao

We study models of weighted exponential random graphs in the large network limit. These models have recently been proposed to model weighted network data arising from a host of applications including socio-econometric data such as migration…

Probability · Mathematics 2018-07-12 Shankar Bhamidi , Suman Chakraborty , Skyler Cranmer , Bruce Desmarais

Consider a random regular graph with degree $d$ and of size $n$. Assign to each edge an i.i.d. exponential random variable with mean one. In this paper we establish a precise asymptotic expression for the maximum number of edges on the…

Probability · Mathematics 2012-10-10 Hamed Amini , Yuval Peres

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

In this paper we consider first-passage percolation on certain 1-dimensional periodic graphs, such as the $\Z\times\{0,1,\ldots,K-1\}^{d-1}$ nearest neighbour graph for $d,K\geq1$. We find that both length and weight of minimal-weight paths…

Probability · Mathematics 2015-04-28 Daniel Ahlberg

In this paper we prove a quantiative local limit theorem for the distribution of the number of triangles in the Erd\H{o}s-Renyi random graph $G(n,p)$, for a fixed $p\in (0,1)$. This proof is an extension of the previous work of Gilmer and…

Combinatorics · Mathematics 2017-03-22 Ross Berkowitz

Graph-limit theory focuses on the convergence of sequences of graphs when the number of nodes becomes arbitrarily large. This framework defines a continuous version of graphs allowing for the study of dynamical systems on very large graphs,…

Probability · Mathematics 2020-05-20 Julien Petit , Renaud Lambiotte , Timoteo Carletti

A \emph{uniform random intersection graph} $G(n,m,k)$ is a random graph constructed as follows. Label each of $n$ nodes by a randomly chosen set of $k$ distinct colours taken from some finite set of possible colours of size $m$. Nodes are…

Combinatorics · Mathematics 2008-12-03 Simon R. Blackburn , Stefanie Gerke

Consider~\(n\) nodes~\(\{X_i\}_{1 \leq i \leq n}\) independently distributed in the unit square~\(S,\) each according to a distribution~\(f.\) Nodes~\(X_i\) and~\(X_j\) are joined by an edge if the Euclidean distance~\(d(X_i,X_j)\) is less…

Probability · Mathematics 2021-03-02 Ghurumuruhan Ganesan

Let $G_n$ be a random geometric graph with vertex set $[n]$ based on $n$ i.i.d.\ random vectors $X_1,\ldots,X_n$ drawn from an unknown density $f$ on $\R^d$. An edge $(i,j)$ is present when $\|X_i -X_j\| \le r_n$, for a given threshold…

Machine Learning · Statistics 2023-11-23 Caelan Atamanchuk , Luc Devroye , Gabor Lugosi
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