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Learning rates of multi-kernel regression by orthogonal greedy algorithm

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Publication:1926541
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DOI10.1016/j.jspi.2012.08.002zbMath1254.62085OpenAlexW1998858903MaRDI QIDQ1926541

Luoqing Li, Hong Chen, Zhibin Pan

Publication date: 28 December 2012

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2012.08.002


zbMATH Keywords

sparselearning ratedata dependent hypothesis spaceRademacher chaos complexitymulti-kernel learning


Mathematics Subject Classification ID

Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).


Related Items (4)

Optimality of the rescaled pure greedy learning algorithms ⋮ Fully corrective gradient boosting with squared hinge: fast learning rates and early stopping ⋮ On the convergence rate of kernel-based sequential greedy regression ⋮ Randomized multi-scale kernels learning with sparsity constraint regularization for regression




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