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Learning the Kernel Matrix with Semidefinite Programming

Journal of Machine Learning Research, (2004): 27-72

Cited: 2855|Views133
EI

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. This information is contained in the so-called kernel matrix...More

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