This work addresses the need for stateful dataflow programs that can rapidly sift through huge, evolving data sets. These data-intensive applications perform complex multi-step c...
Dionysios Logothetis, Christopher Olston, Benjamin...
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
Energy in sensor networks is a distributed, non-transferable resource. Over time, differences in energy availability are likely to arise. Protocols like routing trees may concent...
Geoffrey Werner Challen, Jason Waterman, Matt Wels...
Abstract—Dynamic Demes is a new method for the parallelisation of evolutionary algorithms. It was derived as a combination of two other parallelisation algorithms: the master-sla...
In current embedded systems, one of the major concerns is energy conservation. The dynamic voltage-scheduling (DVS) framework, which involves dynamically adjusting the voltage and...
Ruibin Xu, Chenhai Xi, Rami G. Melhem, Daniel Moss...