In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
The aim of transfer learning is to accelerate learning in related domains. In reinforcement learning, many different features such as a value function and a policy can be transfer...
We discuss problems in developing policies for ground truthing document images for pixel-accurate segmentation. First, we describe ground truthing policies that apply to four diff...
This paper proposes a new scheduling policy for cluster-based servers called DAS (Deferred Assignment Scheduling). The main idea in DAS is to defer scheduling as much as possible,...
Victoria Ungureanu, Benjamin Melamed, Michael N. K...
—Various spectrum management schemes have been proposed in recent years to improve the spectrum utilization in cognitive radio networks. However, few of them have considered the ...
Beibei Wang, Yongle Wu, K. J. Ray Liu, T. Charles ...