We extend the VC theory of statistical learning to data dependent spaces of classifiers. This theory can be viewed as a decomposition of classifier design into two components; the...
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint ...
Abundant content, data type and diverse members' interests naturally lead to preference heterogeneity within a multicast session requiring frequent communication within subgr...
We compare standard global IR searching with user-centric localized techniques to address the database selection problem. We conduct a series of experiments to compare the retriev...
We describe the design of a rule-based language for expressing changes to Haskell programs in a systematic and reliable way. The update language essentially offers update commands...
—Recently, multiresolution visualization methods have become an indispensable ingredient of real-time interactive postprocessing. The enormous databases, typically coming along w...