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We derive an upper bound on the local Rademacher complexity of $\ell_p$-norm multiple kernel learning, which yields a tighter excess risk bound than global approaches.
On the subspaces of L p
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The Cauchy-Schwarz Master Class: An Introduction to the Art of Mathematical Inequalities
J. M. Steele · 2004
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Efficient and accurate lp-norm multiple kernel learning
M. Kloft, U. Brefeld, S. Sonnenburg, P. Laskov, K.-R. Müller, and A. Zien · 2009
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V. Koltchinskii · 2009
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