bandit feedback

Universal Rates for Multiclass Learning with Bandit Feedback COLT 2025 A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning ICLR 2024 Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics COLT 2024 Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs NeurIPS 2024 BanditQ:Fair Bandits with Guaranteed Rewards UAI 2024 Bandits with Knapsacks and Predictions UAI 2024 Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback NeurIPS 2024 Contextual Linear Optimization with Bandit Feedback NeurIPS 2024 Data-Driven Online Model Selection With Regret Guarantees AISTATS 2024 Efficient Online Set-valued Classification with Bandit Feedback ICML 2024 Fast Rates for Bandit PAC Multiclass Classification NeurIPS 2024 From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization NeurIPS 2024 Handling Heterogeneous Curvatures in Bandit LQR Control ICML 2024 Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition AISTATS 2024 Improved learning rates in multi-unit uniform price auctions NeurIPS 2024 Initializing Services in Interactive ML Systems for Diverse Users NeurIPS 2024 Learning Fair Division from Bandit Feedback AISTATS 2024 Multiclass Online Learnability under Bandit Feedback ALT 2024 Nearly Minimax Optimal Submodular Maximization with Bandit Feedback NeurIPS 2024 On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: a regret lower bound for WSU-UX AISTATS 2024 Optimal Clustering with Bandit Feedback JMLR 2024 Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback ICML 2024 Rate-Optimal Policy Optimization for Linear Markov Decision Processes ICML 2024 Sum-max Submodular Bandits AISTATS 2024 Testing the Feasibility of Linear Programs with Bandit Feedback ICML 2024