We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
We study the problem of computing waveletbased synopses for massive data sets in static and streaming environments. A compact representation of a data set is obtained after a thre...
Due to the enormous size of the web and low precision of user queries, finding the right information from the web can be difficult if not impossible. One approach that tries to ...
We consider the problem of approximate range counting over streams of d-dimensional points. In the data stream model, the algorithm makes a single scan of the data, which is prese...
Abstract. The success of a case-based reasoning system depends critically on the relevance of the case base. Much current CBR research focuses on how to compact and refine the con...