Abstract. We present several results related to ranking. We give a general margin-based bound for ranking based on the L∞ covering number of the hypothesis space. Our bound sugge...
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Background: The large gap between the number of protein sequences in databases and the number of functionally characterized proteins calls for the development of a fast computatio...
An object on the Semantic Web is likely to be denoted with multiple URIs by different parties. Object coreference resolution is to identify “equivalent” URIs that denote the ...
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...