Online Algorithms

Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements ICML 2024 Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion AISTATS 2024 Improved Regret for Bandit Convex Optimization with Delayed Feedback NeurIPS 2024 Improved Regret of Linear Ensemble Sampling NeurIPS 2024 Improving Adaptive Online Learning Using Refined Discretization ALT 2024 Information Capacity Regret Bounds for Bandits with Mediator Feedback JMLR 2024 Informative Path Planning with Limited Adaptivity AISTATS 2024 Interpolating Item and User Fairness in Multi-Sided Recommendations NeurIPS 2024 Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling NeurIPS 2024 Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm NeurIPS 2024 Learning-Augmented Algorithms for the Bahncard Problem NeurIPS 2024 Learning-Augmented Algorithms with Explicit Predictors NeurIPS 2024 Learning-Augmented Online Algorithm for Two-Level Ski-Rental Problem AAAI 2024 Learning-Based Algorithms for Graph Searching Problems AISTATS 2024 Learning Fair Division from Bandit Feedback AISTATS 2024 Learning from Snapshots of Discrete and Continuous Data Streams NeurIPS 2024 Learning from Streaming Data when Users Choose ICML 2024 Learning in Online Principal-Agent Interactions: The Power of Menus AAAI 2024 Learning Optimal Tax Design in Nonatomic Congestion Games NeurIPS 2024 Learning to Price Homogeneous Data NeurIPS 2024 Learning with Adaptive Resource Allocation ICML 2024 Learning with Posterior Sampling for Revenue Management under Time-varying Demand IJCAI 2024 Leveraging (Biased) Information: Multi-armed Bandits with Offline Data ICML 2024 Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging AAAI 2024 Linear Causal Bandits: Unknown Graph and Soft Interventions NeurIPS 2024