Managing uncertain data using probabilistic frameworks has attracted much interest lately in the database literature, and a central computational challenge is probabilistic infere...
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...
Abstract—This paper proposes a new software-oriented approach for managing the distributed shared L2 caches of a chip multiprocessor (CMP) for latency-oriented multithreaded appl...
—In this paper, we study the distributed spectrum allocation for autonomous users transmitting delay-sensitive information over a wireless multi-carrier network. Because there is...
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...