Online Algorithms

The Hidden Cost of Approximation in Online Mirror Descent COLT 2026 Truly Adapting to Adversarial Constraints in Constrained MABs COLT 2026 Achieving Õ(√T) Regret in Average-Reward POMDPs with Known Observation Models AISTATS 2025 Adaptive Market Making with Inventory Constraints via Online Learning AAAI 2025 An Online Learning Theory of Trading-Volume Maximization ICLR 2025 Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs AAAI 2025 Competitive Fair Scheduling with Predictions ICLR 2025 CompileAgent: Automated Real-World Repo-Level Compilation with Tool-Integrated LLM-based Agent System ACL 2025 Contextual Bandits with Stage-wise Constraints JMLR 2025 Corruption-Robust Variance-aware Algorithms for Generalized Linear Bandits under Heavy-tailed Rewards UAI 2025 Distribution-Aware Online Learning for Urban Spatiotemporal Forecasting on Streaming Data IJCAI 2025 DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback ICLR 2025 Doubly-Bounded Queue for Constrained Online Learning: Keeping Pace with Dynamics of Both Loss and Constraint AAAI 2025 Efficient Methods for Non-stationary Online Learning JMLR 2025 Event-Driven Online Vertical Federated Learning ICLR 2025 Fast Second-Order Online Kernel Learning Through Incremental Matrix Sketching and Decomposition IJCAI 2025 Feature-Based Online Bilateral Trade ICLR 2025 Improved Regret Bounds for Online Fair Division with Bandit Learning AAAI 2025 Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games ICLR 2025 LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits AISTATS 2025 Learning-Augmented Algorithms for Online Concave Packing and Convex Covering Problems AISTATS 2025 Learning-Augmented Frequent Directions ICLR 2025 Learning from Imperfect Human Feedback: A Tale from Corruption-Robust Dueling ICLR 2025 Lexicographic Lipschitz Bandits: New Algorithms and a Lower Bound JMLR 2025 Lipschitz Bandits in Optimal Space ICLR 2025