In many applications, a reduction of the amount of the original data or a representation of the original data by a small set of variables is often required. Among many techniques, ...
In the context of code coupling, efficient data redistribution is a crucial issue to reach high-performances. However, most of the works in this area have limited their studies to ...
Traditional text classification algorithms are based on a basic assumption: the training and test data should hold the same distribution. However, this identical distribution assum...
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
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 ...