Policy gradient approaches are a powerful instrument for learning how to interact with the environment. Existing approaches have focused on propositional and continuous domains on...
We present an efficient method for maximizing energy functions with first and second order potentials, suitable for MAP labeling estimation problems that arise in undirected graph...
In this paper we consider sampling based fitted value iteration for discounted, large (possibly infinite) state space, finite action Markovian Decision Problems where only a gener...
Intelligent tutoring systems have demonstrated their utility in a variety of domains. However, they are notoriously resource intensive to build. We report here on the development ...
Viswanathan Kodaganallur, Rob R. Weitz, David Rose...
Recent advances in statistical inference and machine learning close the divide between simulation and classical optimization, thereby enabling more rigorous and robust microarchit...