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• W2459835 abstract "In this paper, we give a new sharp generalization bound of lp-MKL which is a generalized framework of multiple kernel learning (MKL) and imposes lp-mixed-norm regularization instead of l1-mixed-norm regularization. We utilize localization techniques to obtain the sharp learning rate. The bound is characterized by the decay rate of the eigenvalues of the associated kernels. A larger decay rate gives a faster convergence rate. Furthermore, we give the minimax learning rate on the ball characterized by lp-mixed-norm in the product space. Then we show that our derived learning rate of lp-MKL achieves the minimax optimal rate on the lp-mixed-norm ball." @default.
• W2459835 created "2016-06-24" @default.
• W2459835 creator A5078812767 @default.
• W2459835 date "2011-03-27" @default.
• W2459835 modified "2023-09-27" @default.
• W2459835 title "Fast Learning Rate of lp-MKL and its Minimax Optimality" @default.
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• W2459835 hasPublicationYear "2011" @default.
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