We present parallel algorithms for building decision-tree classifiers on shared-memory multiprocessor (SMP) systems. The proposed algorithms span the gamut of data and task parall...
Mohammed Javeed Zaki, Ching-Tien Ho, Rakesh Agrawa...
This paper presents a method for updating approximations of a concept incrementally. The results can be used to implement a quasi-incremental algorithm for learning classification...
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
We present further developments in our work on using data from real users to build a probabilistic model of user affect based on Dynamic Bayesian Networks (DBNs) and designed to de...
Voltage scaling reduces leakage power for cache lines unlikely to be referenced soon. Partitioning reduces dynamic power via smaller, specialized structures. We combine approaches,...
Major Bhadauria, Sally A. McKee, Karan Singh, Gary...