We present MBoost, a novel extension to AdaBoost that extends boosting to use multiple weak learners explicitly, and provides robustness to learning models that overfit or are po...
Abstract. This work extends studies of Angluin, Lange and Zeugmann on the dependence of learning on the hypotheses space chosen for the class. In subsequent investigations, uniform...
Abstract— Imitation learning in robots, also called programing by demonstration, has made important advances in recent years, allowing humans to teach context dependant motor ski...
The Grid vision promises the secure and dynamic sharing of heterogeneous resources across the Internet. To date the emphasis has been on supercomputing scenarios where a relatively...
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...