—We present in this paper an integrated solution to rapidly recognizing dynamic objects in surveillance videos by exploring various contextual information. This solution consists...
Xiaobai Liu, Liang Lin, Shuicheng Yan, Hai Jin, We...
In this work we study hybrid approaches to LTL symbolic model checking; that is, approaches that use explicit representations of the property automaton, whose state space is often ...
Roberto Sebastiani, Stefano Tonetta, Moshe Y. Vard...
A key component of any reinforcement learning algorithm is the underlying representation used by the agent. While reinforcement learning (RL) agents have typically relied on hand-...
Designer productivity and design predictability are vital factors for successful embedded system design. Shrinking time-to-market and increasing complexity of these systems requir...
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...