Online Learning

Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data NeurIPS 2024 Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss NeurIPS 2024 Strategic Usage in a Multi-Learner Setting AISTATS 2024 Structured Dynamic Pricing: Optimal Regret in a Global Shrinkage Model JMLR 2024 Testing exchangeability by pairwise betting AISTATS 2024 The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models AAAI 2024 The Limits of Differential Privacy in Online Learning NeurIPS 2024 The Power of Resets in Online Reinforcement Learning NeurIPS 2024 The Predicted-Updates Dynamic Model: Offline, Incremental, and Decremental to Fully Dynamic Transformations COLT 2024 The SMART approach to instance-optimal online learning COLT 2024 Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective NeurIPS 2024 Tight Rates for Bandit Control Beyond Quadratics NeurIPS 2024 Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback ICLR 2024 Universal Online Convex Optimization with $1$ Projection per Round NeurIPS 2024 Universal Test-Time Adaptation Through Weight Ensembling, Diversity Weighting, and Prior Correction WACV 2024 Using Surrogates in Covariate-adjusted Response-adaptive Randomization Experiments with Delayed Outcomes NeurIPS 2024 Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits ICLR 2024 When Is Inductive Inference Possible? NeurIPS 2024 Worst-Case Offline Reinforcement Learning with Arbitrary Data Support NeurIPS 2024 (ε, u)-Adaptive Regret Minimization in Heavy-Tailed Bandits COLT 2024 A Blackbox Approach to Best of Both Worlds in Bandits and Beyond COLT 2023 Active Cost-aware Labeling of Streaming Data AISTATS 2023 Adaptation to the Range in K-Armed Bandits JMLR 2023 Adapting to Continuous Covariate Shift via Online Density Ratio Estimation NeurIPS 2023 Adaptive Linear Estimating Equations NeurIPS 2023