Many data sources on the Web evolve in the sense that they change their content over time, typically as a reaction to some event. Such changes often need to be mirrored in data on...
We study generalization properties of linear learning algorithms and develop a data dependent approach that is used to derive generalization bounds that depend on the margin distr...
In this paper we describe our experience with Teapot [7], a domain-specific language for writing cache coherence protocols. Cache coherence is of concern when parallel and distrib...
Satish Chandra, James R. Larus, Michael Dahlin, Br...
This paper describes conceptionof social robot systemas self-organizing system. Distributed autonomousrobot systemis not autonomousas a group, if the systemtotally depends on the ...
Allowing loads to issue out-of-order with respect to earlier unresolved store addresses is very important for extracting parallelism in large-window superscalar processors. Blindl...