Sumit Sah

Online Learning With Non-convex Losses: New Condition To Achieve Small Dynamic Regret

In this paper, we consider the challenging problem of online learning with non-convex time varying objectives/loss functions. We show that a simple Online gradient descent (OGD) algorithm achieves a dynamic regret comparable to the strongly convex setting provided a new condition that we propose is…