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- W2134899186 abstract "In this paper, we investigate coefficient-based regularized least squares regression problem in a data dependent hypothesis space. The learning algorithm is implemented with samples drawn by unbounded sampling processes and the error analysis is performed by a stepping-stone technique. A new error decomposition technique is proposed for the error analysis. The regularization parameters in our setting provide much more flexibility and adaptivity. Sharp learning rates are addressed by means of l 2 -empirical covering numbers under a moment hypothesis condition." @default.
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- W2134899186 date "2013-12-01" @default.
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- W2134899186 title "CONVERGENCE ANALYSIS OF COEFFICIENT-BASED REGULARIZATION UNDER MOMENT INCREMENTAL CONDITION" @default.
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- W2134899186 doi "https://doi.org/10.1142/s0219691314500088" @default.
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