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147
Processes on unimodular random networks
, 2007
"... We investigate unimodular random networks. Our motivations include their characterization via reversibility of an associated random walk and their similarities to unimodular quasitransitive graphs. We extend various theorems concerning random walks, percolation, spanning forests, and amenability fr ..."
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Cited by 124 (6 self)
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We investigate unimodular random networks. Our motivations include their characterization via reversibility of an associated random walk and their similarities to unimodular quasitransitive graphs. We extend various theorems concerning random walks, percolation, spanning forests, and amenability from the known context of unimodular quasitransitive graphs to the more general context of unimodular random networks. We give properties of a trace associated to unimodular random networks with applications
A survey of maxtype recursive distributional equations
 Annals of Applied Probability 15 (2005
, 2005
"... In certain problems in a variety of applied probability settings (from probabilistic analysis of algorithms to statistical physics), the central requirement is to solve a recursive distributional equation of the form X d = g((ξi,Xi), i ≥ 1). Here(ξi) and g(·) are given and the Xi are independent cop ..."
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Cited by 86 (6 self)
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In certain problems in a variety of applied probability settings (from probabilistic analysis of algorithms to statistical physics), the central requirement is to solve a recursive distributional equation of the form X d = g((ξi,Xi), i ≥ 1). Here(ξi) and g(·) are given and the Xi are independent copies of the unknown distribution X. We survey this area, emphasizing examples where the function g(·) is essentially a “maximum ” or “minimum” function. We draw attention to the theoretical question of endogeny: inthe associated recursive tree process X i,aretheX i measurable functions of the innovations process (ξ i)? 1. Introduction. Write
Asymptotic enumeration of spanning trees
 Combin. Probab. Comput
, 2005
"... Note: Theorem numbers differ from the published version. Abstract. We give new general formulas for the asymptotics of the number of spanning trees of a large graph. A special case answers a question of McKay (1983) for regular graphs. The general answer involves a quantity for infinite graphs that ..."
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Cited by 56 (5 self)
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Note: Theorem numbers differ from the published version. Abstract. We give new general formulas for the asymptotics of the number of spanning trees of a large graph. A special case answers a question of McKay (1983) for regular graphs. The general answer involves a quantity for infinite graphs that we call “tree entropy”, which we show is a logarithm of a normalized determinant of the graph Laplacian for infinite graphs. Tree entropy is also expressed using random walks. We relate tree entropy to the metric entropy of the uniform spanning forest process on quasitransitive amenable graphs, extending a result of Burton and Pemantle (1993). §1. Introduction. Methods of enumeration of spanning trees in a finite graph G and relations to various areas of mathematics and physics have been investigated for more than 150 years. The number of spanning trees is often called the complexity of the graph, denoted here by τ(G). The best known formula for the complexity, proved in every basic text on graph
On exchangeable random variables and the statistics of large graphs and hypergraphs
, 2008
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A Critical Branching Process Model for Biodiversity
, 2008
"... Motivated as a null model for comparison with data, we study the following model for a phylogenetic tree on n extant species. The origin of the clade is a random time in the past, whose (improper) distribution is uniform on (0, ∞). After that origin, the process of extinctions and speciations is a c ..."
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Cited by 43 (5 self)
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Motivated as a null model for comparison with data, we study the following model for a phylogenetic tree on n extant species. The origin of the clade is a random time in the past, whose (improper) distribution is uniform on (0, ∞). After that origin, the process of extinctions and speciations is a continuoustime critical branching process of constant rate, conditioned on having the prescribed number n of species at the present time. We study various mathematical properties of this model as n → ∞ limits: time of origin and of most recent common ancestor; pattern of divergence times within lineage trees; time series of numbers of species; number of extinct species in total, or ancestral to extant species; and “local” structure of the tree itself. We emphasize several mathematical techniques: associating walks with trees, a point process representation of lineage trees, and Brownian limits.
Network Externalities and the Deployment of Security Features
 and Protocols in the Internet. ACM SIGMETRICS 08
"... Getting new security features and protocols to be widely adopted and deployed in the Internet has been a continuing challenge. There are several reasons for this, in particular economic reasons arising from the presence of network externalities. Indeed, like the Internet itself, the technologies to ..."
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Cited by 42 (10 self)
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Getting new security features and protocols to be widely adopted and deployed in the Internet has been a continuing challenge. There are several reasons for this, in particular economic reasons arising from the presence of network externalities. Indeed, like the Internet itself, the technologies to secure it exhibit network effects: their value to individual users changes as other users decide to adopt them or not. In particular, the benefits felt by early adopters of security solutions might fall significantly below the cost of adoption, making it difficult for those solutions to gain attraction and get deployed at a large scale. Our goal in this paper is to model and quantify the impact of such externalities on the adoptability and deployment of security features and protocols in the Internet. We study a network of interconnected agents, which are subject to epidemic
Maximum Weight Independent Sets and Matchings in Sparse Random Graphs. Exact Results Using the Local Weak Convergence Method
, 2005
"... Let G(n, c/n) and Gr(n) be an nnode sparse random graph and a sparse random rregular graph, respectively, and let I(n, r) and I(n, c) be the sizes of the largest independent set in G(n, c/n) and Gr(n). The asymptotic value of I(n, c)/n as n →∞, can be computed using the KarpSipser algorithm when ..."
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Cited by 38 (9 self)
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Let G(n, c/n) and Gr(n) be an nnode sparse random graph and a sparse random rregular graph, respectively, and let I(n, r) and I(n, c) be the sizes of the largest independent set in G(n, c/n) and Gr(n). The asymptotic value of I(n, c)/n as n →∞, can be computed using the KarpSipser algorithm when c ≤ e. For random cubic graphs, r = 3, it is only known that.432 ≤ lim infn I(n,3)/n ≤ lim sup n I(n,3)/n ≤.4591 with high probability (w.h.p.) as n →∞, as shown in Frieze and Suen [Random Structures Algorithms 5 (1994), 649–664] and Bollabas [European J Combin 1 (1980), 311–316], respectively. In this paper we assume in addition that the nodes of the graph are equipped with nonnegative weights, independently generated according to some common distribution, and we consider instead the maximum weight of an independent set. Surprisingly, we discover that for certain weight distributions, the limit limn I(n, c)/n can be computed exactly even when c> e, and limn I(n, r)/n can be computed exactly for some r ≥ 1. For example, when the weights are exponentially distributed with parameter 1, limn I(n,2e)/n ≈.5517, and limn I(n,3)/n ≈.6077. Our results are established using the recently developed local weak convergence method further reduced to a certain local optimality property exhibited by the models we
Laws of large numbers in stochastic geometry with statistical applications
, 2007
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Ising models on locally treelike graphs
, 2008
"... Abstract We consider Ising models on graphs that converge locally to trees. Examples include random regulargraphs with bounded degree and uniformly random graphs with bounded average degree. We prove that the `cavity ' prediction for the limiting free energy per spin is correct for any temperat ..."
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Cited by 35 (4 self)
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Abstract We consider Ising models on graphs that converge locally to trees. Examples include random regulargraphs with bounded degree and uniformly random graphs with bounded average degree. We prove that the `cavity ' prediction for the limiting free energy per spin is correct for any temperature and externalfield. Further, local marginals can be approximated by iterating a set of mean field (cavity) equations. Both results are achieved by proving the local convergence of the Boltzmann distribution on the originalgraph to the Boltzmann distribution on the appropriate infinite random tree. 1 Introduction An Ising model on the finite graph G (with vertex set V, and edge set E) is defined by the following Boltzmann distributions over x = {xi: i 2 V}, with xi 2 {+1,1}