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Multi-Armed Bandits

1044 directly classified papers

Papers per year

Papers

Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification NIPS 2022
Smoothed Adversarial Linear Contextual Bandits with Knapsacks ICML 2022
Trading Off Resource Budgets For Improved Regret Bounds NIPS 2022
Optimal and Efficient Dynamic Regret Algorithms for Non-Stationary Dueling Bandits ICML 2022
Breaking the $\sqrtT$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits ICML 2022
Best Heuristic Identification for Constraint Satisfaction IJCAI 2022
Factored DRO: Factored Distributionally Robust Policies for Contextual Bandits NIPS 2022
Deep Hierarchy in Bandits ICML 2022
A Reduction from Linear Contextual Bandits Lower Bounds to Estimations Lower Bounds ICML 2022
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees NIPS 2022
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits ICML 2022
Regret Minimization with Performative Feedback ICML 2022
Inverse Contextual Bandits: Learning How Behavior Evolves over Time ICML 2022
IMED-RL: Regret optimal learning of ergodic Markov decision processes NIPS 2022
Towards Off-Policy Learning for Ranking Policies with Logged Feedback AAAI 2022
Differentially Private Regret Minimization in Episodic Markov Decision Processes AAAI 2022
Fixed-Budget Best-Arm Identification in Structured Bandits IJCAI 2022
Effective Dimension in Bandit Problems under Censorship NIPS 2022
Instance Dependent Regret Analysis of Kernelized Bandits ICML 2022
Multi-slots Online Matching with High Entropy ICML 2022
No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation NIPS 2022
A Unifying Theory of Thompson Sampling for Continuous Risk-Averse Bandits AAAI 2022
Learning in Congestion Games with Bandit Feedback NIPS 2022
When Combinatorial Thompson Sampling meets Approximation Regret NIPS 2022
An $\alpha$-No-Regret Algorithm For Graphical Bilinear Bandits NIPS 2022