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Multi-Armed Bandits

1,057 papers

Papers per year

5
27
87
38
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Papers

Fairness of Exposure in Stochastic Bandits ICML 2021
Addressing the Long-term Impact of ML Decisions via Policy Regret IJCAI 2021
Human-AI Collaboration with Bandit Feedback IJCAI 2021
Epsilon Best Arm Identification in Spectral Bandits IJCAI 2021
Mean Field Equilibrium in Multi-Armed Bandit Game with Continuous Reward IJCAI 2021
Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare IJCAI 2021
AI for Planning Public Health Interventions IJCAI 2021
AutoBandit: A Meta Bandit Online Learning System IJCAI 2021
Regulating Greed Over Time in Multi-Armed Bandits JMLR 2021
Preference-based Online Learning with Dueling Bandits: A Survey JMLR 2021
On Multi-Armed Bandit Designs for Dose-Finding Trials JMLR 2021
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits JMLR 2021
A Contextual Bandit Bake-off JMLR 2021
Refined approachability algorithms and application to regret minimization with global costs JMLR 2021
Thompson Sampling Algorithms for Cascading Bandits JMLR 2021
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals JMLR 2021
Linear Bandits on Uniformly Convex Sets JMLR 2021
Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning L4DC 2021
Reward Biased Maximum Likelihood Estimation for Reinforcement Learning L4DC 2021
Matrix games with bandit feedback UAI 2021
Bandits with partially observable confounded data UAI 2021
CORe: Capitalizing On Rewards in Bandit Exploration UAI 2021
Efficient Contextual Bandits with Continuous Actions NIPS 2020
Delay and Cooperation in Nonstochastic Linear Bandits NIPS 2020
A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling NIPS 2020