We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...
In recent years, academic literature has analyzed many attacks on network trace anonymization techniques. These attacks usually correlate external information with anonymized data...
Martin Burkhart, Dominik Schatzmann, Brian Trammel...
In many networks, vertices have hidden attributes that are correlated with the network's topology. For instance, in social networks, people are more likely to be friends if t...
We study query processing in large graphs that are fundamental data model underpinning various social networks and Web structures. Given a set of query nodes, we aim to find the g...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...