Reviews: Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction

This paper shows that "certain" adversarial prediction problems under multivariate losses can be solved "much faster than they used to be". The paper stands on two main ideas: (1) that the general saddle function optimization problem stated in eq. The paper is quite focused on the idea of obtaining a faster solution of the adversarial problem. However, the key simplification is applied to a specific loss, the F-score, so one may wonder if the benefits of the proposed method could be extended to other losses. The extension of the SVRG is a more general result, it seems that the paper could have been focused on proposing Breg-SVRG, showing the adversarial optimization with the F-score as a particular application.