Dynamic Regret in Online Convex Optimization with Indicator Switching Costs
Dynamic regret with fixed switching penalties, via a meta-learning framework that is minimax-optimal for piecewise-constant comparators.
On the Dynamic Regret of Following the Regularized Leader: Optimism with History Pruning
Dynamic-regret analysis of FTRL with optimistic predictions and a history-pruning technique that improves bounds.