Online Algorithms

Optimal Hardness of Online Algorithms for Large Common Induced Subgraphs COLT 2026 Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs COLT 2026 Ordinal Secretaries with Advice AAAI 2026 Provably Efficient Multi-Objective Bandit Algorithms Under Preference-Centric Customization AAAI 2026 Quantum Lipschitz Bandits AAAI 2026 Refined Risk Bounds for Unbounded Losses via Transductive Priors JMLR 2026 Right Branches Matter in Failure-based Variable Ordering Heuristics AAAI 2026 Sequential Selling with Sunk Cost Bias AAAI 2026 Strategy-robust Online Learning in Contextual Pricing ALT 2026 The Hidden Cost of Approximation in Online Mirror Descent COLT 2026 Universal Dynamic Regret and Constraint Violation Bounds for Constrained Online Convex Optimization ALT 2026 Active Learning with Selective Time-Step Acquisition for PDEs ICML 2025 Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback JMLR 2025 Adaptive Data Collection for Robust Learning Across Multiple Distributions ICML 2025 Adaptive Merchant-Centric Risk Control via Unbiased Decision-Making and Dynamic Optimization in E-Commerce AAAI 2025 Adaptive Sample Sharing for Multi Agent Linear Bandits ICML 2025 Adversarial Combinatorial Semi-bandits with Graph Feedback ICML 2025 A Dynamic Penalization Framework for Online Rank-1 Semidefinite Programming Relaxations L4DC 2025 A Game-Theoretic Perspective on Inconsistency Handling IJCAI 2025 AKORN: Adaptive Knots generated Online for RegressioN splines ICML 2025 Algorithmic Recourse for Long-Term Improvement ICML 2025 Algorithms with Calibrated Machine Learning Predictions ICML 2025 Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits ICLR 2025 Alternating Regret for Online Convex Optimization COLT 2025 An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems. ALT 2025