Running Data Grid applications such as High Energy Nuclear Physics (HENP) and weather modelling experiments involves working with huge data sets possibly of hundreds of Terabytes ...
We present techniques for discovering and exploiting regularity in large curvilinear data sets. The data can be based on a single mesh or a mesh composed of multiple submeshes (al...
We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of obse...
Multi-dimensional spatial data are obtained when a number of data acquisition devices are deployed at different locations to measure a certain set of attributes of the study subje...
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...