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Related papers: De-Preferential Attachment Random Graphs

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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

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

A version of ``preferential attachment'' random graphs, corresponding to linear ``weights'' with random ``edge additions,'' which generalizes some previously considered models, is studied. This graph model is embedded in a continuous-time…

Probability · Mathematics 2007-05-23 K. B. Athreya , A. P. Ghosh , S. Sethuraman

We analyze a dynamic random undirected graph in which newly added vertices are connected to those already present in the graph either using, with probability $p$, an anti-preferential attachment mechanism or, with probability $1-p$, a…

Probability · Mathematics 2020-12-11 Umberto De Ambroggio , Federico Polito , Laura Sacerdote

We propose a random graph model with preferential attachment rule and \emph{edge-step functions} that govern the growth rate of the vertex set. We study the effect of these functions on the empirical degree distribution of these random…

Probability · Mathematics 2019-01-09 Caio Alves , Rodrigo Ribeiro , Remy Sanchis

We prove almost sure convergence of the maximum degree in an evolving tree model combining local choice and preferential attachment. At each step in the growth of the graph, a new vertex is introduced. A fixed, finite number of possible…

Probability · Mathematics 2014-03-19 Yury Malyshkin , Elliot Paquette

We study preferential attachment mechanisms in random graphs that are parameterized by (i) a constant bias affecting the degree-biased distribution on the vertex set and (ii) the distribution of times at which new vertices are created by…

Probability · Mathematics 2017-10-09 Benjamin Bloem-Reddy , Peter Orbanz

We prove almost sure convergence of the maximum degree in an evolving graph model combining a growing number of local choices with sublinear preferential attachment. At each step in the growth of the graph, a new vertex is introduced. Then…

Probability · Mathematics 2019-11-19 Yury Malyshkin

We consider a preferential attachment model that incorporates an anomaly. Our goal is to understand the evolution of the network before and after the occurrence of the anomaly by studying the influence of the anomaly on the structural…

Physics and Society · Physics 2025-05-07 Qiu Liang , Remco van der Hofstad , Nelly Litvak

A preferential attachment model for a growing network incorporating deletion of edges is studied and the expected asymptotic degree distribution is analyzed. At each time step $t=1,2,\ldots$, with probability $\pi_1>0$ a new vertex with one…

Physics and Society · Physics 2015-09-30 Maria Deijfen , Mathias Lindholm

We consider a preferential attachment random graph with self-reinforcement. Each time a new vertex comes in, it attaches itself to an old vertex with a probability that is proportional to the sum of the degrees of that old vertex at all…

Probability · Mathematics 2025-07-29 Yogesh Dahiya , Frank den Hollander

We consider an evolving preferential attachment random graph model where at discrete times a new node is attached to an old node, selected with probability proportional to a superlinear function of its degree. For such schemes, it is known…

Probability · Mathematics 2017-04-20 Sunder Sethuraman , Shankar C. Venkataramani

In this paper, a random graph process ${G(t)}_{t\geq 1}$ is studied and its degree sequence is analyzed. Let $(W_t)_{t\geq 1}$ be an i.i.d. sequence. The graph process is defined so that, at each integer time $t$, a new vertex, with $W_t$…

Probability · Mathematics 2020-06-05 Maria Deijfen , Henri van den Esker , Remco van der Hofstad , Gerard Hooghiemstra

We define a dynamic model of random networks, where new vertices are connected to old ones with a probability proportional to a sublinear function of their degree. We first give a strong limit law for the empirical degree distribution, and…

Probability · Mathematics 2008-07-31 Steffen Dereich , Peter Morters

We provide optimal rates of convergence to the asymptotic distribution of the (properly scaled) degree of a fixed vertex in two preferential attachment random graph models. Our approach is to show that these distributions are unique fixed…

Probability · Mathematics 2013-03-15 Erol A. Peköz , Adrian Röllin , Nathan Ross

A variation of the preferential attachment random graph model of Barab\'asi and Albert is defined that incorporates planted communities. The graph is built progressively, with new vertices attaching to the existing ones one-by-one. At every…

Machine Learning · Statistics 2018-01-30 Bruce Hajek , Suryanarayana Sankagiri

We study an asymptotical behavior of the maximal degree in the degree distribution in an evolving tree model combining the local choice and the Mori's preferential attachment. In the considered model, the random graph is constructed in the…

Probability · Mathematics 2017-10-27 Yury Malyshkin

We find assimpotics for the first $k$ highest degrees of the degree distribution in an evolving tree model combining the local choice and the preferential attachment. In the considered model, the random graph is constructd in the following…

Probability · Mathematics 2016-08-31 Yury Malyshkin

We introduce a new type of preferential attachment tree that includes choices in its evolution, like with Achlioptas processes. At each step in the growth of the graph, a new vertex is introduced. Two possible neighbor vertices are selected…

Probability · Mathematics 2014-02-18 Yury Malyshkin , Elliot Paquette

We deal with a general preferential attachment graph model with multiple type edges. The types are chosen randomly, in a way that depends on the evolution of the graph. In the $N$-type case, we define the (generalized) degree of a given…

Probability · Mathematics 2019-03-25 Ágnes Backhausz , Bence Rozner
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