dynamic regret

Zeroth-Order Non-Convex Learning via Hierarchical Dual Averaging ICML 2021 Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-Sizes NeurIPS 2020 Adaptive Online Estimation of Piecewise Polynomial Trends NeurIPS 2020 Adversarial Blocking Bandits NeurIPS 2020 A Simple Approach for Non-stationary Linear Bandits AISTATS 2020 A Simple Online Algorithm for Competing with Dynamic Comparators UAI 2020 Bandit Convex Optimization in Non-stationary Environments AISTATS 2020 Distributed Online Optimization over a Heterogeneous Network with Any-Batch Mirror Descent ICML 2020 Dynamic Regret of Convex and Smooth Functions NeurIPS 2020 Dynamic Regret of Policy Optimization in Non-Stationary Environments NeurIPS 2020 Minimizing Dynamic Regret and Adaptive Regret Simultaneously AISTATS 2020 Online Learning in Changing Environments IJCAI 2020 Online Learning with Continuous Variations: Dynamic Regret and Reductions AISTATS 2020 Optimizing for the Future in Non-Stationary MDPs ICML 2020 Parameter-free, Dynamic, and Strongly-Adaptive Online Learning ICML 2020 Randomized Exploration for Non-Stationary Stochastic Linear Bandits UAI 2020 Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism ICML 2020 The Power of Predictions in Online Control NeurIPS 2020 Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information COLT 2019 Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes COLT 2019 A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal and Parameter-free COLT 2019 Improved Path-length Regret Bounds for Bandits COLT 2019 Learning to Optimize under Non-Stationarity AISTATS 2019 Online Forecasting of Total-Variation-bounded Sequences NeurIPS 2019 Online Optimal Control with Linear Dynamics and Predictions: Algorithms and Regret Analysis NeurIPS 2019