Multi-armed bandit

Friday, September 15, 2017 - 3:00pm - 3:30pm
Yuhong Yang (University of Minnesota, Twin Cities)
In practice of medicine, multiple treatments are often available to treat individual patients. The task of identifying the best treatment for a specific patient is very challenging due to patient inhomogeneity. Multi-armed bandit with covariates provides a framework for designing effective treatment allocation rules in a way that integrates the learning from experimentation with maximizing the benefits to the patients along the process.
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