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February  2020, 3(1): 25-40. doi: 10.3934/mfc.2020003

Error analysis on regularized regression based on the Maximum correntropy criterion

 School of Mathematical Science, Zhejiang University, Hangzhou, 310027, China

* Corresponding author: Bingzheng Li

Received  December 2019 Published  February 2020

This paper aims at the regularized learning algorithm for regression associated with the correntropy induced losses in reproducing kernel Hilbert spaces. The main target is the error analysis for the regression problem in learning theory based on the maximum correntropy. Explicit learning rates are provided. From our analysis, when choosing a suitable parameter of the loss function, we obtain satisfactory learning rates. The rates depend on the regularization error and the covering numbers of the reproducing kernel Hilbert space.

Citation: Bingzheng Li, Zhengzhan Dai. Error analysis on regularized regression based on the Maximum correntropy criterion. Mathematical Foundations of Computing, 2020, 3 (1) : 25-40. doi: 10.3934/mfc.2020003
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