AUC is an important performance measure and many algorithms have been devoted to AUC optimization, mostly by minimizing a surrogate convex loss on a training data set. In this work, we focus on one-pass AUC optimization that requires going through the training data only once without storing the entire training dataset, where conventional online learning algorithms cannot be applied directly bec...