Online Algorithms

Dueling Bandits with Team Comparisons NeurIPS 2021 Dueling Convex Optimization ICML 2021 Dynamic Balancing for Model Selection in Bandits and RL ICML 2021 Dynamic Planning and Learning under Recovering Rewards ICML 2021 Efficient Algorithms for Stochastic Repeated Second-price Auctions ALT 2021 Efficient Bandit Convex Optimization: Beyond Linear Losses COLT 2021 Efficient Online Estimation of Causal Effects by Deciding What to Observe NeurIPS 2021 Efficient Online Learning for Dynamic k-Clustering ICML 2021 Expert advice problem with noisy low rank loss ACML 2021 Exponential Weights Algorithms for Selective Learning COLT 2021 Fairness and Bias in Online Selection ICML 2021 Faster Game Solving via Predictive Blackwell Approachability: Connecting Regret Matching and Mirror Descent AAAI 2021 Federated Multi-Armed Bandits AAAI 2021 Generating Adversarial Disturbances for Controller Verification L4DC 2021 Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization NeurIPS 2021 Hybrid Regret Bounds for Combinatorial Semi-Bandits and Adversarial Linear Bandits NeurIPS 2021 Impossible Tuning Made Possible: A New Expert Algorithm and Its Applications COLT 2021 Improved Analysis of the Tsallis-INF Algorithm in Stochastically Constrained Adversarial Bandits and Stochastic Bandits with Adversarial Corruptions COLT 2021 Improved Regret Bound and Experience Replay in Regularized Policy Iteration ICML 2021 Improved Regret for Zeroth-Order Stochastic Convex Bandits COLT 2021 Kernel-Based Reinforcement Learning: A Finite-Time Analysis ICML 2021 Lazy OCO: Online Convex Optimization on a Switching Budget COLT 2021 Learning-to-learn non-convex piecewise-Lipschitz functions NeurIPS 2021 Learning to Price Against a Moving Target ICML 2021 Leveraging Good Representations in Linear Contextual Bandits ICML 2021