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Found 2 papers, 1 papers with code
A Bayesian Approach to Online Learning for Contextual Restless Bandits with Applications to Public Health
Restless multi-armed bandits (RMABs) are used to model sequential resource allocation in public health intervention programs.
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
In this work, we develop the Mixture Adaptive Design (MAD), a new experimental design for multi-armed bandits that enables continuous inference on the ATE with guarantees on statistical validity and power for nearly any bandit algorithm.
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