Online Algorithms

Riemannian Projection-free Online Learning NeurIPS 2023 Robust Algorithms on Adaptive Inputs from Bounded Adversaries ICLR 2023 Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees. ICML 2023 Small Total-Cost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness NeurIPS 2023 Smooth Non-stationary Bandits ICML 2023 Speeding Up Bellman Ford via Minimum Violation Permutations ICML 2023 Speed-Oblivious Online Scheduling: Knowing (Precise) Speeds is not Necessary ICML 2023 Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds NeurIPS 2023 Stochastic No-regret Learning for General Games with Variance Reduction ICLR 2023 Streaming Active Learning with Deep Neural Networks ICML 2023 The Gain from Ordering in Online Learning NeurIPS 2023 Tight Regret Bounds for Single-pass Streaming Multi-armed Bandits ICML 2023 Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts ICML 2023 Treepiece: Faster Semantic Parsing via Tree Tokenization EMNLP 2023 TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation AISTATS 2023 U-Calibration: Forecasting for an Unknown Agent COLT 2023 Unconstrained Online Learning with Unbounded Losses ICML 2023 Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach NeurIPS 2023 Variance-Aware Sparse Linear Bandits ICLR 2023 Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency COLT 2023 Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory ACML 2023 VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback JMLR 2023 Active Evaluation: Efficient NLG Evaluation with Few Pairwise Comparisons ACL 2022 Algorithms with Prediction Portfolios NeurIPS 2022 Alternating Mirror Descent for Constrained Min-Max Games NeurIPS 2022