We studied a number of measures that characterize the difficulty of a classification problem. We compared a set of real world problems to random combinations of points in this mea...
We address the problem of rate allocation and network/path selection for multiple users, running simultaneous applications over multiple parallel access networks. Our joint optimi...
Dan Jurca, Wolfgang Kellerer, Eckehard G. Steinbac...
We present the IBM systems submitted and evaluated within the CLEAR'06 evaluation campaign for the tasks of single person visual 3D tracking (localization) and 2D face trackin...
We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
The selection of features for classification, clustering and approximation is an important task in pattern recognition, data mining and soft computing. For real-valued features, th...