Many applications rely heavily on large amounts of data in the distributed storages collected over time or produced by large scale scientific experiments or simulations. The key co...
As the capture and analysis of single-time-point microarray expression data becomes routine, investigators are turning to time-series expression data to investigate complex gene r...
Selnur Erdal, Ozgur Ozturk, David L. Armbruster, H...
The DWS (Data Warehouse Striping) technique is a data partitioning approach especially designed for distributed data warehousing environments. In DWS the fact tables are distribute...
Raquel Almeida, Jorge Vieira, Marco Vieira, Henriq...
Existing meta-learning based distributed data mining approaches do not explicitly address context heterogeneity across individual sites. This limitation constrains their applicatio...
Yan Xing, Michael G. Madden, Jim Duggan, Gerard Ly...
A precondition of existing ensemble-based distributed data mining techniques is the assumption that contributing data are identically and independently distributed. However, this a...
Yan Xing, Michael G. Madden, Jim Duggan, Gerard Ly...