Common techniques tackling the task of classification in data mining employ ansatz functions associated to training data points to fit the data as well as possible. Instead, the fe...
: In this presentation, a short outline of the history of past and present Grid projects in research and industry is given, followed by some near- and long-term Grid scenarios and ...
Grid workflow can be defined as the composition of grid application services which execute on heterogeneous and distributed resources in a well-defined order to accomplish a speci...
Recently we presented a new approach [20] to the classification problem arising in data mining. It is based on the regularization network approach but in contrast to other methods...
Sparse grid methods represent a powerful and efficient technique for the representation and approximation of functions and particularly the solutions of partial differential equat...