Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
The minimum-distance classifier summarizes each class with a prototype and then uses a nearest neighbor approach for classification. Three drawbacks of the original minimum-distan...
Integrating Deep Web sources requires highly accurate semantic matches between the attributes of the source query interfaces. These matches are usually established by comparing th...
Abstract. The explicit management of Quality of Service (QoS) of network connectivity, such as, e.g., working cost, transaction support, and security, is a key requirement for the ...
Rocco De Nicola, Gian Luigi Ferrari, Ugo Montanari...
Abstract. It is well known that diversity among component classifiers is crucial for constructing a strong ensemble. Most existing ensemble methods achieve this goal through resam...