Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Next generation Web 2.0 communities and distributed P2P systems rely on the cooperation of diverse user populations spread across numerous administrative and security domains. Zero...
Gayatri Swamynathan, Kevin C. Almeroth, Ben Y. Zha...
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Many online networks are measured and studied via sampling techniques, which typically collect a relatively small fraction of nodes and their associated edges. Past work in this a...
Maciej Kurant, Minas Gjoka, Yan Wang, Zack W. Almq...
We propose a new approach to ensure privacy in location based services, without requiring any support from a"trusted" entity. We observe that users of location based ser...