This paper considers the ERM scheme for quantile regression. We conduct error analysis for this learning algorithm by means of a variance-expectation bound when a noise condition is satisfied for the underlying probability measure. The learning rates are derived by applying concentration techniques involving the -empirical covering numbers.
"ERM Scheme for Quantile Regression." Abstr. Appl. Anal. 2013 (SI32) 1 - 6, 2013. https://doi.org/10.1155/2013/148490