Online Algorithms

A Switching Framework for Online Interval Scheduling with Predictions AAAI 2026 A Theoretical Model for Grit in Pursuing Ambitious Ends AAAI 2026 Bandit Learning for Online Scheduling with Immediate Decision UAI 2026 Bandit Learning in Housing Markets AAAI 2026 Breadth-First Search vs. Restarting Random Walks for Escaping Uninformed Heuristic Regions AAAI 2026 Calibeating Made Simple COLT 2026 City Sampling for Citizens’ Assemblies AAAI 2026 Constrained Online Convex Optimization with Memory and Predictions AAAI 2026 CoRE-Learning with Look-Ahead and Immediate Resource Allocation AAAI 2026 Decentralized Online Convex Optimization with Unknown Feedback Delays AAAI 2026 Efficient Contextual Bandit Learning via Reward-Space Sampling and Online Optimization (Student Abstract) AAAI 2026 Fairness-Aware Design for Contextual Experiments: Guaranteeing Reliability and Equity in Heterogeneous Subgroups AAAI 2026 Fairness in the Multi-Secretary Problem AAAI 2026 Flickering Multi-Armed Bandits L4DC 2026 Graph-Dependent Regret Bounds in Multi-Armed Bandits with Interference UAI 2026 Improved Streaming Algorithm for Fair k-Center Clustering AAAI 2026 Inference Offloading for Cost-Sensitive Binary Classification at the Edge AAAI 2026 Multiple-play Stochastic Bandits with Prioritized Arm Capacity Sharing AAAI 2026 Online Caching in Tree Networks: Algorithms, Regret, and Complexity L4DC 2026 Online Capacitated General Matching with Knapsack AAAI 2026 Online Convex Optimization with Sublinear Noisy Probes COLT 2026 Online Fair Allocations with Binary Valuations and Beyond AAAI 2026 Online Linear Regression with Paid Stochastic Features AAAI 2026 Online Tracking with Predictions for Nonlinear Systems with Koopman Linear Embedding L4DC 2026 On the Robustness of Bandit Multiple Testing AAAI 2026