Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...
Data Warehouses (DWs) use an omnipresent time dimension for keeping track of changes in measure values. However, this dimension cannot be used to model changes in other dimensions...
Natural fractured media are highly unpredictable because of existing complex structures at the fracture and at the network levels. Fractures are by themselves heterogeneous objects...
One of the pillars of trust-worthy computing is process isolation, the ability to keep process data private from other processes running on the same device. While embedded operati...
Herwin Chan, Patrick Schaumont, Ingrid Verbauwhede