2018
Online Learning with Non-Convex Losses and Non-Stationary Regret
AISTATS 2018poster
In this paper, we consider online learning with non-convex loss functions. Similar to Besbes et al. [2015] we apply non-stationary regret as the performance metric. In particular, we study the regret bounds under different assumptions on the information available regarding the loss functions. When t…