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Péter L. Erdős (Rényi Institute, Budapest): How to sample scalefree degree sequence's realizations uniformly and fast 



Friday, 12. April 2019, 10:30  12:30


Abstract.
Because of the important roles of the Internet and social networks in modern society, much attention has been paid to analyzing graphs with realworld network properties. One of the most prominent traits of many realworld networks is that their degree distribution follows the socalled powerlaw, usually with parameter \gamma between 2 and 3. Graphs with such degree distributions are sparse but have vertices with very large degrees. There are peculiarly few available methods to sample the realizations of exact degree distribution uniformly. One of them a newly developed exact uniform sampler by Gao and Wormald (SODA, 2018), based on the configuration model. This works when the parameter \gamma is > 2.8810. Another approach is a newly developed version of the switch Markov chains, which suitable to sample powerlaw degree sequences with parameter \gamma >2. 
Location : Bolyai Intézet, I. emelet, Riesz terem, Aradi Vértanúk tere 1., Szeged 
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