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Multi-Armed Bandits

1,057 papers

Papers per year

5
27
87
38
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Papers

Stochastic Bandits with Delay-Dependent Payoffs AISTATS 2020
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems AISTATS 2020
Stochastic Linear Contextual Bandits with Diverse Contexts AISTATS 2020
A PTAS for the Bayesian Thresholding Bandit Problem AISTATS 2020
On Thompson Sampling for Smoother-than-Lipschitz Bandits AISTATS 2020
Causal Bayesian Optimization AISTATS 2020
Optimal $δ$-Correct Best-Arm Selection for Heavy-Tailed Distributions ALT 2020
DORB: Dynamically Optimizing Multiple Rewards with Bandits EMNLP 2020
Learning with Good Feature Representations in Bandits and in RL with a Generative Model ICML 2020
Budgeted Online Influence Maximization ICML 2020
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020
Optimistic Policy Optimization with Bandit Feedback ICML 2020
A Markov Decision Process Model for Socio-Economic Systems Impacted by Climate Change ICML 2020
Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits ICML 2020
Adaptive Estimator Selection for Off-Policy Evaluation ICML 2020
Thompson Sampling via Local Uncertainty ICML 2020
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound ICML 2020
Neural Contextual Bandits with UCB-based Exploration ICML 2020
Bayesian Decision Process for Budget-efficient Crowdsourced Clustering IJCAI 2020
Best Arm Identification in Spectral Bandits IJCAI 2020
Combinatorial Multi-Armed Bandits with Concave Rewards and Fairness Constraints IJCAI 2020
Multi-Feedback Bandit Learning with Probabilistic Contexts IJCAI 2020
Efficient and Robust High-Dimensional Linear Contextual Bandits IJCAI 2020
Multi-Player Bandits: The Adversarial Case JMLR 2020
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting JMLR 2020