A multi-object operation incurs communication or synchronization overhead when the requested objects are distributed over different nodes. The object pair correlations (the probab...
When training Support Vector Machine (SVM), selection of a training data set becomes an important issue, since the problem of overfitting exists with a large number of training da...
Abstract: Advances in technology now make it possible to integrate hundreds of cores (e.g. general or special purpose processors, embedded memories, application specific components...
In this paper, a multiobjective (MO) learning approach to image feature extraction is described, where Pareto-optimal interest point (IP) detectors are synthesized using genetic p...
The goal of data fusion is to combine several representations of one real world object into a single, consistent representation, e.g., in data integration. A very popular operator...