We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Network coding is a method for achieving channel capacity in networks. The key idea is to allow network routers to linearly mix packets as they traverse the network so that recipi...
Shweta Agrawal, Dan Boneh, Xavier Boyen, David Man...
This paper describes our framework to annotate events using personal and social network contexts. The problem is important as the correct context is critical to effective annotati...
In this paper we study message flow processes in distributed simulators of open queueing networks. We develop and study queueing models for distributed simulators with maximum loo...
Abstract— Sensor networks are being increasingly deployed for collecting critical data in various applications. Once deployed, a sensor network may experience faults at the indiv...
Douglas Herbert, Yung-Hsiang Lu, Saurabh Bagchi, Z...