online learning

Towards Stable Test-time Adaptation in Dynamic Wild World ICLR 2023 Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts ICML 2023 Trading-off price for data quality to achieve fair online allocation NeurIPS 2023 Training Deep Surrogate Models with Large Scale Online Learning ICML 2023 Tree Learning: Optimal Sample Complexity and Algorithms AAAI 2023 U-Calibration: Forecasting for an Unknown Agent COLT 2023 Unconstrained Online Learning with Unbounded Losses ICML 2023 Understanding the Role of Feedback in Online Learning with Switching Costs ICML 2023 Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach NeurIPS 2023 Warm-Start Actor-Critic: From Approximation Error to Sub-optimality Gap ICML 2023 Warm-Starting Nested Rollout Policy Adaptation with Optimal Stopping AAAI 2023 What can online reinforcement learning with function approximation benefit from general coverage conditions? ICML 2023 When Can We Track Significant Preference Shifts in Dueling Bandits? NeurIPS 2023 When Online Learning Meets ODE: Learning without Forgetting on Variable Feature Space AAAI 2023 ActiveHedge: Hedge meets Active Learning ICML 2022 Adapting to Online Label Shift with Provable Guarantees NeurIPS 2022 Adaptive Bandit Convex Optimization with Heterogeneous Curvature COLT 2022 Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits ICML 2022 Adaptive Oracle-Efficient Online Learning NeurIPS 2022 Adaptive Orthogonal Projection for Batch and Online Continual Learning AAAI 2022 Adversarial Tracking Control via Strongly Adaptive Online Learning with Memory AISTATS 2022 A Lyapunov-Based Methodology for Constrained Optimization with Bandit Feedback AAAI 2022 An Analysis of Ensemble Sampling NeurIPS 2022 An Asymptotically Optimal Batched Algorithm for the Dueling Bandit Problem NeurIPS 2022 A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs NeurIPS 2022