ADAM: A Method for Stochastic Optimization (REVIEW)

Adam: A Method for Stochastic Optimization (2015). Diederik P. Kingma and Jimmy Lei Ba. Conference paper at ICLR 2015.

Overview

  • This method computes individual adaptive learning rates for different parameters from estimates of first and second moments of the gradients.
  • Combines AdaGrad (which works well with sparse gradients) and RMSProp (works well in on-line and non-stationary settings.