We study the problem of approximately answering aggregation queries using sampling. We observe that uniform sampling performs poorly when the distribution of the aggregated attrib...
On-line boosting allows to adapt a trained classifier to changing environmental conditions or to use sequentially available training data. Yet, two important problems in the on-li...
Helmut Grabner, Horst Bischof, Jan Sochman, Jiri M...
In this paper we propose a real-time method for tracking hands through image sequences. Our method combines efficiently calculated color likelihood maps with a state-ofthe-art int...
Document clustering techniques have been applied in several areas, with the web as one of the most recent and influent. Both general-purpose and text-oriented techniques exist and...
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...