Large repositories of source code create new challenges and opportunities for statistical machine learning. Here we first develop Sourcerer, an infrastructure for the automated c...
Erik Linstead, Paul Rigor, Sushil Krishna Bajracha...
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit ...
Motivated by increased concern over energy consumption in modern data centers, we propose a new, distributed computing platform called Nano Data Centers (NaDa). NaDa uses ISP-cont...
Vytautas Valancius, Nikolaos Laoutaris, Laurent Ma...
Recently, decentralized publish-subscribe (pub-sub) systems have gained popularity as a scalable asynchronous messaging paradigm over wide-area networks. Most existing pub-sub sys...
Jianxia Chen, Lakshmish Ramaswamy, David Lowenthal