We consider the degree distributions of preferential attachment ran-dom graph models with choice similar to those considered in recent work by Malyshkin and Paquette and Krapivsky and Redner. In these models a new vertex chooses r vertices according to a preferential rule and connects to the vertex in the selection with the sth highest degree. For meek choice, where s> 1, we show that both double exponential decay of the degree distribution and condensation-like behaviour are possible, and provide a criterion to distinguish between them. For greedy choice, where s = 1, we confirm that the degree distribution asympotically follows a power law with logarithmic correction when r = 2 and shows condensation-like be-haviour when r> 2. AMS 2...
In a 2-parameter scale free model of random graphs it is shown that the asymptotic degree distributi...
We study preferential attachment models where vertices enter the network with i.i.d. random numbers ...
The design of algorithms on complex networks, such as rout-ing, ranking or recommendation algorithms...
We consider the preferential attachment model with location-based choice introduced by Haslegrave et...
We introduce a new model of a preferential attachment based random graph which extends the family of...
Abstract. We introduce a new type of preferential attachment tree that includes choices in its evolu...
Abstract. We prove almost sure convergence of the maximum degree in an evolving tree model combining...
In this paper, a random graph process {G(t)}t≥1 is studied and its degree sequence is analyzed. Let ...
In this paper, a random graph process {G(t)}t≥1 is studied and its degree sequence is analyzed. Let ...
In this paper, a random graph process {G(t)} (ta parts per thousand yen1) is studied and its degree ...
We consider the preferential attachment model with location-based choice introduced by Haslegrave et...
We deal with a general preferential attachment graph model with multiple type edges. The types are c...
A random graph evolution mechanism is defined. The evolution studied is a combination of the prefere...
We investigate the use of stochastic approximation as a method of identifying conditions necessary t...
We study the basic preferential attachment process, which generates a sequence of random trees, each...
In a 2-parameter scale free model of random graphs it is shown that the asymptotic degree distributi...
We study preferential attachment models where vertices enter the network with i.i.d. random numbers ...
The design of algorithms on complex networks, such as rout-ing, ranking or recommendation algorithms...
We consider the preferential attachment model with location-based choice introduced by Haslegrave et...
We introduce a new model of a preferential attachment based random graph which extends the family of...
Abstract. We introduce a new type of preferential attachment tree that includes choices in its evolu...
Abstract. We prove almost sure convergence of the maximum degree in an evolving tree model combining...
In this paper, a random graph process {G(t)}t≥1 is studied and its degree sequence is analyzed. Let ...
In this paper, a random graph process {G(t)}t≥1 is studied and its degree sequence is analyzed. Let ...
In this paper, a random graph process {G(t)} (ta parts per thousand yen1) is studied and its degree ...
We consider the preferential attachment model with location-based choice introduced by Haslegrave et...
We deal with a general preferential attachment graph model with multiple type edges. The types are c...
A random graph evolution mechanism is defined. The evolution studied is a combination of the prefere...
We investigate the use of stochastic approximation as a method of identifying conditions necessary t...
We study the basic preferential attachment process, which generates a sequence of random trees, each...
In a 2-parameter scale free model of random graphs it is shown that the asymptotic degree distributi...
We study preferential attachment models where vertices enter the network with i.i.d. random numbers ...
The design of algorithms on complex networks, such as rout-ing, ranking or recommendation algorithms...