Quantile regression has become a popular alternative to least squares for providing comprehensive description of the response distribution, and robustness against heavy-tailed error distributions. However, nonsmooth quantile loss poses new challenges distributed estimation in both computation theoretical development. To address this challenge, we use convolution-type smoothing approach its Tayl...