Solution path for quantile regression with epsilon-insensitive loss in a reproducing kernel Hilbert space

This article proposes an algorithm for finding the solution paths of estimated quantile functions as the regularization parameter varies. The solution paths constitute a useful tool for choosing the optimal regularization parameter.