Abstract
We consider the problem of learning on a compact metric space X in a functional analytic framework. For a dense subalgebra of Lip(X), the space of all Lipschitz functions on X, the Representer Theorem is derived. We obtain exact solutions in the case of least square minimization and regularization and suggest an approximate solution for the Lipschitz classifier.
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© 2004 Springer-Verlag Berlin Heidelberg
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Minh, H.Q., Hofmann, T. (2004). Learning Over Compact Metric Spaces. In: Shawe-Taylor, J., Singer, Y. (eds) Learning Theory. COLT 2004. Lecture Notes in Computer Science(), vol 3120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27819-1_17
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DOI: https://doi.org/10.1007/978-3-540-27819-1_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22282-8
Online ISBN: 978-3-540-27819-1
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