Abstract
We study Mercer’s theorem and feature maps for several positive definite kernels that are widely used in practice. The smoothing properties of these kernels will also be explored.
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© 2006 Springer-Verlag Berlin Heidelberg
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Minh, H.Q., Niyogi, P., Yao, Y. (2006). Mercer’s Theorem, Feature Maps, and Smoothing. In: Lugosi, G., Simon, H.U. (eds) Learning Theory. COLT 2006. Lecture Notes in Computer Science(), vol 4005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11776420_14
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DOI: https://doi.org/10.1007/11776420_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35294-5
Online ISBN: 978-3-540-35296-9
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