This paper presents an efficient and homogeneous paradigm for automatic acquisition and recognition of nonparametric shapes. Acquisition time varies from linear to cubic in the nu...
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
In this paper, we present a low complexity Modulo-PCM based coding algorithm for high speed video cameras used in applications that demand very high frame rates. By compressing th...
In this paper we introduce the idea of snapshot queries for energy efficient data acquisition in sensor networks. Network nodes generate models of their surrounding environment th...
lative Novelty to Identify Useful Temporal Abstractions in Reinforcement Learning ?Ozg?ur S?im?sek ozgur@cs.umass.edu Andrew G. Barto barto@cs.umass.edu Department of Computer Scie...