2021
Efficient Generalization with Distributionally Robust Learning
NeurIPS 2021poster
Distributionally robust learning (DRL) is increasingly seen as a viable method to train machine learning models for improved model generalization. These min-max formulations, however, are more difficult to solve. We provide a new stochastic gradient descent algorithm to efficiently solve this DRL form…