Sampling is a widely used technique to increase efficiency in database and data mining applications operating on large dataset. In this paper we present a scalable sampling imple...
Although many image processing applications are ideally suited for parallel implementation, most researchers in imaging do not benefit from high performance computing on a daily b...
As grid computation systems become larger and more complex, manually diagnosing failures in jobs becomes impractical. Recently, machine-learning techniques have been proposed to d...
Hierarchical clustering methods are important in many data mining and pattern recognition tasks. In this paper we present an efficient coarse grained parallel algorithm for Single...
The problem of counting specified combinations of a given set of variables arises in many statistical and data mining applications. To solve this problem, we introduce the PDtree...
Chad Scherrer, Nathaniel Beagley, Jarek Nieplocha,...