Multiclass problems with binary SVM classifiers are commonly treated as a decomposition in several binary sub-problems. An open question is how to properly tune all these sub-prob...
The paper proposes a method to keep the tracker robust to background clutters by online selecting discriminative features from a large feature space. Furthermore, the feature sele...
Abstract. Previous evaluations of server selection methods for federated search have either used metrics which are unconnected with user satisfaction, or have not been able to acco...
In this work, a new learning paradigm called target selection is proposed, which can be used to test for associations between a single genetic variable and a multidimensional, qua...
Johannes Mohr, Sambu Seo, Imke Puis, Andreas Heinz...
This paper reviews the progress of negative selection algorithms, an anomaly/change detection approach in Artificial Immune Systems (AIS). Following its initial model, we try to ...