Before revision:  With a momentum-based variance reduction technique, PStorm can achieve a near-optimal complexity result (\varepsilon^{-3}) to produce a stochastic \varepsilon-stationary solution, if a mean-squared smoothness condition holds  . Different from existing near-optimal methods, PStorm requires  only one or O(1) samples in every update.
After revision:  With a momentum-based variance reduction technique, PStorm can achieve a near-optimal complexity result (\varepsilon^{-3}) to produce a stochastic \varepsilon-stationary solution, if a mean-squared smoothness condition holds and \Theta(\varepsilon^{-1 . Different from existing near-optimal methods, PStorm requires only one or O(1) samples in every update.