Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
In real-life temporal scenarios, uncertainty and preferences are often essential, coexisting aspects. We present a formalism where temporal constraints with both preferences and un...
Francesca Rossi, Kristen Brent Venable, Neil Yorke...
We consider a non-preemptive, stochastic parallel machine scheduling model with the goal to minimize the weighted completion times of jobs. In contrast to the classical stochastic ...
In partially observable worlds with many agents, nested beliefs are formed when agents simultaneously reason about the unknown state of the world and the beliefs of the other agen...
Luke S. Zettlemoyer, Brian Milch, Leslie Pack Kael...
Abstract. This paper presents algorithms and data structures that exploit a compositional and hierarchical specification to enable more efficient symbolic modelchecking. We encod...