2021
On Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems
AAAI 2021technical
The regret bound of dynamic online learning algorithms is often expressed in terms of the variation in the function sequence (V_T) and/or the path-length of the minimizer sequence after T rounds. For strongly convex and smooth functions, Zhang et al. (2017) establish the squared path-length of the m…