The Acheson J. Duncan Lecture Series: AMS Seminar: Susan Murphy (Harvard University) @ Maryland 110

Title: Online Experimentation and Learning Algorithms in a Clinical Trial
Abstract:  In this talk we describe two reinforcement learning algorithms we have implemented in a mobile health physical activity trial. These algorithms are designed to tackle two challenges faced by mobile health. The first challenge is that while most treatments delivered by a mobile device have immediate nonnegative (hopefully positive) effects, longer term effects tend to be negative due to user burden. To address this first challenge we add a low variance proxy for the delay effects to the reward (e.g. immediate response) in the learning algorithm. The second challenge is that data on any one individual is very noisy making it difficult for the algorithm to learn. To address this challenge we pool data across participants.
Bio: Susan Murphy is Professor of Statistics at Harvard University, Radcliffe Alumnae Professor at the Radcliffe Institute, Harvard University, and Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences.  Her lab works on clinical trial designs and learning algorithms for developing mobile health policies.   She is a 2013 MacArthur Fellow, a member of the National Academy of Sciences and the National Academy of Medicine, both of the US National Academies.  She is currently President of the Institute of Mathematical Statistics.
Susan Murphy’s website is http://people.seas.harvard.edu/~samurphy/