We extend in this paper the concept of the P-admissible floorplan representation to that of the P*-admissible one. A P*-admissible representation can model the most general floorp...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
In this paper we describe a practical framework for studying the navigational behavior of the users of an e-learning environment integrated in a virtual campus. The students navig...