On the Rates of Convergence from Surrogate Risk Minimizers to the Bayes Optimal Classifier

11 Feb 2018 Jingwei Zhang Tongliang Liu DaCheng Tao

We study the rates of convergence from empirical surrogate risk minimizers to the Bayes optimal classifier. Specifically, we introduce the notion of \emph{consistency intensity} to characterize a surrogate loss function and exploit this notion to obtain the rate of convergence from an empirical surrogate risk minimizer to the Bayes optimal classifier, enabling fair comparisons of the excess risks of different surrogate risk minimizers... (read more)

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