When we learn a new motor skill, we have to contend with both the variability inherent in our sensors and the task. The sensory uncertainty can be reduced by using information abo...
We present and derive a new stick-breaking construction of the beta process. The construction is closely related to a special case of the stick-breaking construction of the Dirich...
John William Paisley, Aimee Zaas, Christopher W. W...
Abstract. We consider an upper confidence bound algorithm for Markov decision processes (MDPs) with deterministic transitions. For this algorithm we derive upper bounds on the onl...
We consider how state similarity in average reward Markov decision processes (MDPs) may be described by pseudometrics. Introducing the notion of adequate pseudometrics which are we...
We propose a novel dependent hierarchical Pitman-Yor process model for discrete data. An incremental Monte Carlo inference procedure for this model is developed. We show that infe...