multi-armed bandit

Addressing the Long-term Impact of ML Decisions via Policy Regret IJCAI 2021 Adversarial Dueling Bandits ICML 2021 Adversarial Linear Contextual Bandits with Graph-Structured Side Observations AAAI 2021 A Gang of Adversarial Bandits NeurIPS 2021 A Hybrid Bandit Framework for Diversified Recommendation AAAI 2021 AI for Planning Public Health Interventions IJCAI 2021 AI for Social Good: Between My Research and the Real World AAAI 2021 (Almost) Free Incentivized Exploration from Decentralized Learning Agents NeurIPS 2021 Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits ICML 2021 An Algorithm for Stochastic and Adversarial Bandits with Switching Costs ICML 2021 A One-Size-Fits-All Solution to Conservative Bandit Problems AAAI 2021 Approximation Theory Based Methods for RKHS Bandits ICML 2021 Asymptotically Best Causal Effect Identification with Multi-Armed Bandits NeurIPS 2021 Auditing Black-Box Prediction Models for Data Minimization Compliance NeurIPS 2021 AutoBandit: A Meta Bandit Online Learning System IJCAI 2021 Bandit algorithms: Letting go of logarithmic regret for statistical robustness AISTATS 2021 Bandit Learning with Delayed Impact of Actions NeurIPS 2021 Bandit Phase Retrieval NeurIPS 2021 Bandit Quickest Changepoint Detection NeurIPS 2021 Bandits Don’t Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits EMNLP 2021 Bandits with Knapsacks beyond the Worst Case NeurIPS 2021 Bandits with many optimal arms NeurIPS 2021 Batched Thompson Sampling NeurIPS 2021 Best Arm Identification in Graphical Bilinear Bandits ICML 2021 Best Model Identification: A Rested Bandit Formulation ICML 2021