YES VI and the Workshop Statistics of Complex Networks: theory and applications
Nowadays technology allows the monitoring and studying of extremely complex networked systems such as neuronal, metabolic, social, and computer networks. The extremely complex nature of these systems and the dramatic growth in dataset sizes gives rise to important and challenging research questions: how to perform meaningful statistical inference from very large and noisy data sets? Which properties of these complex systems can be inferred from such data? Can sound inference methodologies be also made computationally feasible?