In this paper we investigate multi-task learning in the context of Gaussian Processes (GP). We propose a model that learns a shared covariance function on input-dependent features...
Edwin V. Bonilla, Kian Ming Chai, Christopher K. I...
Recent research in decision theoretic planning has focussedon making the solution of Markov decision processes (MDPs) more feasible. We develop a family of algorithms for structur...
Craig Boutilier, Ronen I. Brafman, Christopher W. ...
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Attentive vision is characterized by selective sensing in space and time as well as selective processing with respect to a specic task. Selection in space involves the splitting ...
We present the design and development of a data stream system that captures data uncertainty from data collection to query processing to final result generation. Our system focuse...
Yanlei Diao, Boduo Li, Anna Liu, Liping Peng, Char...