Curveball: a new generation of sampling algorithms for graphs with fixed degree sequence
نویسندگان
چکیده
The switching model is a Markov chain approach to sample graphs with fixed degree sequence uniformly at random. The recently invented Curveball algorithm [35] for bipartite graphs applies several switches simultaneously (‘trades’). Here, we introduce Curveball algorithms for simple (un)directed graphs which use single or simultaneous trades. We show experimentally that these algorithms converge magnitudes faster than the corresponding switching models.
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ورودعنوان ژورنال:
- CoRR
دوره abs/1609.05137 شماره
صفحات -
تاریخ انتشار 2016