Comparing optimal bounding ellipsoid and support vector machine active learning

In this paper we propose two active learning algorithms combining statistical active learning methods based on SVM and optimal bounding algorithms (OBE) of adaptive system identification. We unify SVM and OBE by demonstrating the similarities and representing SVM in the OBE interpretation. Samples are judiciously selected based on a volume measure provided by OBE using both simple heuristic and greedy optimal strategies. Preliminary experiments illustrate the effectiveness of the proposed algorithms as compared to similar methods.