A PhD thesis on Semi-supervised learning with Graphs by Xiaojin Zhu. Focuses on creating graphs, based on a mixture of labeled and unlabeled data (as per the semi-supervised learning paradigm) and using processes on these graphs to propagate in rigo

A PhD thesis by Peter Mahlmann. Devoted to design and implementation of P2P networks, based on random graphs. It creates a low-latency model for a P2P network, based on random graph theory. Contains links to a Java implementation of the prototype.