We derive continuous-time batch and online versions of the recently introduced efficient O(N2 ) training algorithm of Atiya and Parlos [2000] for fully recurrent networks. A mathem...
An algorithm has been developed to dynamically schedule heterogeneous tasks on heterogeneous processors in a distributed system. The scheduler operates in an environment with dynam...
In this paper we report some of the research endeavors we are embarking on as part of the Doctoral research of the first author. We have already completed an investigation of some...
We formalize the associative bandit problem framework introduced by Kaelbling as a learning-theory problem. The learning environment is modeled as a k-armed bandit where arm payof...
Alexander L. Strehl, Chris Mesterharm, Michael L. ...
We consider the problem of online learning in a changing environment under sparse user feedback. Specifically, we address the classification of music types according to a user...