This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Estimating characteristics of large graphs via sampling is a vital part of the study of complex networks. Current sampling methods such as (independent) random vertex and random w...
: A fundamental problem in communication networks is wavelength assignment (WA): given a set of routing paths on a network, assign a wavelength to each path such that the paths wit...
Abstract. We investigate the degree distribution resulting from graph generation models based on rank-based attachment. In rank-based attachment, all vertices are ranked according ...
Abstract. We analyze special random network models – so-called thickened trees – which are constructed by random trees where the nodes are replaced by local clusters. These obj...
Michael Drmota, Bernhard Gittenberger, Reinhard Ku...