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bandit feedback

158 papers

Papers

Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret COLT 2026 Efficient Decentralized Learning of Generalized Quantal Response Equilibrium UAI 2026 Learning from Equivalence Queries, Revisited COLT 2026 Online Market Making and the Value of Observing the Order Book COLT 2026 Policy Optimization for Adversarial Linear Mixture MDPs with Unknown Transitions and Bandit Feedback UAI 2026 Truly Adapting to Adversarial Constraints in Constrained MABs COLT 2026 Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback JMLR 2025 Adaptive Threshold Sampling for Pure Exploration in Submodular Bandits UAI 2025 Best of Both Worlds: Regret Minimization versus Minimax Play ICML 2025 Clustering Items through Bandit Feedback: Finding the Right Feature out of Many ICML 2025 Clustering with bandit feedback: breaking down the computation/information gap ALT 2025 Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries COLT 2025 Fixed-Budget Change Point Identification in Piecewise Constant Bandits AISTATS 2025 Fixed-Confidence Multiple Change Point Identification under Bandit Feedback ICML 2025 For Universal Multiclass Online Learning, Bandit Feedback and Full Supervision are Equivalent ALT 2025 Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback COLT 2025 Learning Adversarial MDPs with Stochastic Hard Constraints ICML 2025 Learning Imperfect Information Extensive-form Games with Last-iterate Convergence under Bandit Feedback ICML 2025 Linear Submodular Maximization with Bandit Feedback AISTATS 2025 Non-stochastic Budgeted Online Pricing with Semi-Bandit Feedback AAAI 2025 Online Learning of Coalition Structures by Selfish Agents AAAI 2025 Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting AAAI 2025 Policy Optimization for CMDPs with Bandit Feedback: Learning Stochastic and Adversarial Constraints ICML 2025 Single-agent Poisoning Attacks Suffice to Ruin Multi-Agent Learning ICLR 2025 The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback ICML 2025