YellowFin is an auto-tuning optimizer based on momentum SGD which requires no manual specification of learning rate and momentum. It measures the objective landscape on-the-fly and tune momentum as well as learning rate using local quadratic approximation.

The implementation here can be a drop-in replacement for any optimizer in MXNet (So far we only implemented and tested upon SGD and other optimizers are in the to-do list).

For more technical details, please refer to the paper YellowFin and the Art of Momentum Tuning.