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Abstract: Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. (Update)
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BibTeX entry: (Update)
@misc{ gert-journal,
author = "Gert Lanckriet Gert",
title = "Journal of Machine Learning Research 5 (2004) 27-72 Submitted 10/02; Revised
8/03; Published 1/04 Learning the Kernel Matrix with Semidefinite Programming",
url = "citeseer.ist.psu.edu/756650.html" }
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