Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
This paper presents a new learning approach for pattern classification applications involving imbalanced data sets. In this approach, a clustering technique is employed to resamp...
Giang Hoang Nguyen, Abdesselam Bouzerdoum, Son Lam...
For difficult prediction problems, practitioners often segment the data into relatively homogenous groups and then build a model for each group. This two-step procedure usually res...
High speed bulk data transfer is an important part of many data-intensive scientific applications. This paper describes an aggressive bulk data transfer scheme, called Reliable Bl...
Eric He, Jason Leigh, Oliver T. Yu, Thomas A. DeFa...
The exceptional growth of graphics hardware in programmability and data processing speed in the past few years has fuelled extensive research in using it for general purpose compu...