We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
In this paper, we propose a novel manifold alignment method by learning the underlying common manifold with supervision of corresponding data pairs from different observation sets...
Deming Zhai, Bo Li, Hong Chang, Shiguang Shan, Xil...
Spatial Alarms are reminders for mobile users upon their arrival of certain spatial location of interest. Spatial alarm processing requires meeting two demanding objectives: high ...
Abstract. In exploratory learning environments, learners can use different strategies to solve a problem. To the designer or teacher, however, not all these strategies are known in...
We consider Discrete Event Systems (DES) involving tasks with real-time constraints and seek to control processing times so as to minimize a cost function subject to each task mee...