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08/15/2023
Dyadic Reinforcement Learning
Mobile health aims to enhance health outcomes by delivering intervention...
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07/26/2023
Online learning in bandits with predicted context
We consider the contextual bandit problem where at each time, the agent ...
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06/19/2023
Effect-Invariant Mechanisms for Policy Generalization
Policy learning is an important component of many real-world learning sy...
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05/29/2023
Contextual Bandits with Budgeted Information Reveal
Contextual bandit algorithms are commonly used in digital health to reco...
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04/11/2023
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling
There is a growing interest in using reinforcement learning (RL) to pers...
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12/01/2022
Modeling Mobile Health Users as Reinforcement Learning Agents
Mobile health (mHealth) technologies empower patients to adopt/maintain ...
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11/25/2022
Doubly robust nearest neighbors in factor models
In this technical note, we introduce an improved variant of nearest neig...
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02/14/2022
Counterfactual inference for sequential experimental design
We consider the problem of counterfactual inference in sequentially desi...
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07/21/2021
Online structural kernel selection for mobile health
Motivated by the need for efficient and personalized learning in mobile ...
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12/21/2020
Fast Physical Activity Suggestions: Efficient Hyperparameter Learning in Mobile Health
Users can be supported to adopt healthy behaviors, such as regular physi...
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07/31/2020
IntelligentPooling: Practical Thompson Sampling for mHealth
In mobile health (mHealth) smart devices deliver behavioral treatments r...
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07/23/2020
Batch Policy Learning in Average Reward Markov Decision Processes
We consider the batch (off-line) policy learning problem in the infinite...
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04/13/2020
Power-Constrained Bandits
Contextual bandits often provide simple and effective personalization in...
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03/30/2020
Translating Behavioral Theory into Technological Interventions: Case Study of an mHealth App to Increase Self-reporting of Substance-Use Related Data
Mobile health (mHealth) applications are a powerful medium for providing...
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02/23/2020
Rapidly Personalizing Mobile Health Treatment Policies with Limited Data
In mobile health (mHealth), reinforcement learning algorithms that adapt...
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12/30/2019
Off-Policy Estimation of Long-Term Average Outcomes with Applications to Mobile Health
With the recent advancements in wearables and sensing technology, health...
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09/08/2019
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity
With the recent evolution of mobile health technologies, health scientis...
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12/02/2018
Personalizing Intervention Probabilities By Pooling
In many mobile health interventions, treatments should only be delivered...
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11/09/2017
