Online Learning

Robust and Computationally Efficient Linear Contextual Bandits under Adversarial Corruption and Heavy-Tailed Noise UAI 2026 Robust Online Learning ALT 2026 Sample-Efficient Omniprediction for Proper Losses COLT 2026 Self-Concordant Perturbations for Linear Bandits COLT 2026 Self-Normalized Martingales and Uniform Regret Bounds for Linear Regression COLT 2026 Sharp analysis of linear ensemble sampling COLT 2026 Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction COLT 2026 Stability of Certainty-Equivalent Adaptive LQR for Linear Systems with Unknown Time-Varying Parameters L4DC 2026 Swap Regret Minimization Through Response-Based Approachability COLT 2026 TALON: Test-time Adaptive Learning for On-the-Fly Category Discovery CVPR 2026 TESO: Online Tracking of Essential Matrix by Stochastic Optimization CVPR 2026 The Hidden Cost of Approximation in Online Mirror Descent COLT 2026 Toward Simultaneously Optimal Regret in U-Calibration COLT 2026 Truly Adapting to Adversarial Constraints in Constrained MABs COLT 2026 Worst-case Error Bounds for Online Learning of Smooth Functions COLT 2026 AdaO2B: Adaptive Online to Batch Conversion for Out-of-Distribution Generalization AAAI 2025 Adapting to Online Distribution Shifts in Deep Learning: A Black-Box Approach AISTATS 2025 Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback JMLR 2025 Adaptive Market Making with Inventory Constraints via Online Learning AAAI 2025 A Deployed Online Reinforcement Learning Algorithm in an Oral Health Clinical Trial AAAI 2025 An Online Learning Theory of Trading-Volume Maximization ICLR 2025 A Novel Sparse Active Online Learning Framework for Fast and Accurate Streaming Anomaly Detection Over Data Streams IJCAI 2025 Anytime-Valid A/B Testing of Counting Processes AISTATS 2025 Approximate information maximization for bandit games AISTATS 2025 Approximate Thompson Sampling for Learning Linear Quadratic Regulators with O(√T) Regret L4DC 2025