ADAM: A Method for Stochastic Optimization
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.