Training neural networks using learned optimizers

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training neural networks using learned optimizers. One of method is for training a neural network layer comprising a plurality of network parameters having a plurality of dimensions each having a plurality of indices, the method comprising: maintaining a set of values corresponding to respective sets of indices of each dimension, each value representing a measure of central tendency of past gradients of the network parameters having an index in the dimension that is in the set of indices; performing a training step to obtain a new gradient for each network parameter; updating each set of values using the new gradients; and for each network parameter: generating an input from the updated sets of values; processing the input using an optimizer neural network to generate an output defining an update for the network parameter; and applying the update.