# SGD and quantile regression

It is my understanding that the quantile loss is not differentiable (at 0) so base gradient descent cannot be used.

However, Vowpal Wabbit which is an SGD-based learner very much includes quantile regression, and calculates the derivative as:

float e = label - prediction;
if(e == 0) return 0;
return e > 0 ? -tau : (1-tau);


Am I missing something here? Is this an accepted way to use SGD with QR?