Online Algorithms

Instance-Sensitive Algorithms for Pure Exploration in Multinomial Logit Bandit AAAI 2022 Jointly Efficient and Optimal Algorithms for Logistic Bandits AISTATS 2022 k-experts - Online Policies and Fundamental Limits AISTATS 2022 Learning-Augmented Algorithms for Online Linear and Semidefinite Programming NeurIPS 2022 Learning-Augmented Algorithms for Online Steiner Tree AAAI 2022 Learning from a Learning User for Optimal Recommendations ICML 2022 Learning from a Sample in Online Algorithms NeurIPS 2022 Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context NeurIPS 2022 Learning in Congestion Games with Bandit Feedback NeurIPS 2022 Learning on the Edge: Online Learning with Stochastic Feedback Graphs NeurIPS 2022 Learning Predictions for Algorithms with Predictions NeurIPS 2022 Learning the Optimal Recommendation from Explorative Users AAAI 2022 Learning to Control Linear Systems can be Hard COLT 2022 Learning to Identify Top Elo Ratings: A Dueling Bandits Approach AAAI 2022 Learning to Plan Variable Length Sequences of Actions with a Cascading Bandit Click Model of User Feedback AISTATS 2022 Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions NeurIPS 2022 Linear Bandit Algorithms with Sublinear Time Complexity ICML 2022 Lipschitz Bandits with Batched Feedback NeurIPS 2022 Luckiness in Multiscale Online Learning NeurIPS 2022 Machine Learning for Online Algorithm Selection under Censored Feedback AAAI 2022 Matching in Multi-arm Bandit with Collision NeurIPS 2022 Maximizing Revenue under Market Shrinkage and Market Uncertainty NeurIPS 2022 Mechanism Design with Predictions IJCAI 2022 Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification NeurIPS 2022 Minimax Regret for Cascading Bandits NeurIPS 2022