bandit feedback

Understanding the Role of Feedback in Online Learning with Switching Costs ICML 2023 A Lyapunov-Based Methodology for Constrained Optimization with Bandit Feedback AAAI 2022 Distributed Online Convex Optimization with Compressed Communication NeurIPS 2022 Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback NeurIPS 2022 Learning in Congestion Games with Bandit Feedback NeurIPS 2022 Learning on the Edge: Online Learning with Stochastic Feedback Graphs NeurIPS 2022 Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback NeurIPS 2022 New Projection-free Algorithms for Online Convex Optimization with Adaptive Regret Guarantees COLT 2022 One Gradient Frank-Wolfe for Decentralized Online Convex and Submodular Optimization ACML 2022 Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback ICML 2022 Policy Optimization for Stochastic Shortest Path COLT 2022 Revisiting Online Submodular Minimization: Gap-Dependent Regret Bounds, Best of Both Worlds and Adversarial Robustness ICML 2022 Risk-Averse No-Regret Learning in Online Convex Games ICML 2022 Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games NeurIPS 2022 Scale-Free Adversarial Multi Armed Bandits ALT 2022 Sequential Blocked Matching AAAI 2022 Beyond Bandit Feedback in Online Multiclass Classification NeurIPS 2021 Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback AAAI 2021 Efficient Bandit Convex Optimization: Beyond Linear Losses COLT 2021 Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case ICML 2021 Human-AI Collaboration with Bandit Feedback IJCAI 2021 Learning from eXtreme Bandit Feedback AAAI 2021 Matrix games with bandit feedback UAI 2021 Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition COLT 2021 No-regret learning with high-probability in adversarial Markov decision processes UAI 2021