Online Learning

Self-Directed Linear Classification COLT 2023 Smoothed Online Combinatorial Optimization Using Imperfect Predictions AAAI 2023 Smoothed Online Learning for Prediction in Piecewise Affine Systems NeurIPS 2023 Sorting and Hypergraph Orientation under Uncertainty with Predictions IJCAI 2023 Stochastic Contextual Bandits with Long Horizon Rewards AAAI 2023 Stochastic Gradient Succeeds for Bandits ICML 2023 The Sample Complexity of Approximate Rejection Sampling With Applications to Smoothed Online Learning COLT 2023 Towards Utilitarian Online Learning -- A Review of Online Algorithms in Open Feature Space IJCAI 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 Tree Learning: Optimal Sample Complexity and Algorithms AAAI 2023 Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory ACML 2023 Vector Optimization with Stochastic Bandit Feedback AISTATS 2023 When Online Learning Meets ODE: Learning without Forgetting on Variable Feature Space AAAI 2023 ActiveHedge: Hedge meets Active Learning ICML 2022 Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization AISTATS 2022 Adapting to Online Label Shift with Provable Guarantees NeurIPS 2022 Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds COLT 2022 Adversarial Tracking Control via Strongly Adaptive Online Learning with Memory AISTATS 2022 Algorithms with Prediction Portfolios NeurIPS 2022 A Lyapunov-Based Methodology for Constrained Optimization with Bandit Feedback AAAI 2022 A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs NeurIPS 2022 An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization AISTATS 2022 An Online Learning Approach to Sequential User-Centric Selection Problems AAAI 2022 Anonymous Bandits for Multi-User Systems NeurIPS 2022