Learning rates of least-square regularized regression with polynomial kernels

DOI10.1007/S11425-008-0137-5zbMath1186.68374OpenAlexW2134876593MaRDI QIDQ1041518

Guo Mao Wang, Bing-Zheng Li

Publication date: 2 December 2009

Published in: Science in China. Series A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11425-008-0137-5

zbMATH Keywords

learning theoryregularization scheme

Mathematics Subject Classification ID

General nonlinear regression (62J02) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

On the need for structure modelling in sequence prediction ⋮ The convergence rates of Shannon sampling learning algorithms ⋮ Optimal rate of the regularized regression learning algorithm

Cites Work

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• ESTIMATING THE APPROXIMATION ERROR IN LEARNING THEORY
• SVM Soft Margin Classifiers: Linear Programming versus Quadratic Programming
• Theory of Reproducing Kernels

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