Constraints applied on classic frequent patterns are too strict and may cause interesting patterns to be missed. Hence, researchers have proposed to mine a more relaxed version of...
In this report we address the problem of static scheduling of realtime systems that include both hard and soft tasks. We consider systems in which both hard and soft tasks are per...
Recently, there has been an increased focus on modeling uncertainty by distributions. Suppose we wish to compute a function of a stream whose elements are samples drawn independen...
We address the problem of computing approximate answers to continuous sliding-window joins over data streams when the available memory may be insufficient to keep the entire join...
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...