Collaborative optimization problems can often be modeled as a linear program whose objective function and constraints combine data from several parties. However, important applicat...
It has been shown that network coding can lead to significant improvement in network capacity and reduction in power consumption for multicast traffic in wireless networks. In this...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
This paper proposes a method to construct an adaptive agent that is universal with respect to a given class of experts, where each expert is designed specifically for a particular...
We discuss optimal design problems for a popular method of series estimation in regression problems. Commonly used design criteria are based on the generalized variance of the est...