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Power Constrained Bandits.

, , , , and . MLHC, volume 149 of Proceedings of Machine Learning Research, page 209-259. PMLR, (2021)

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Introduction to Part III: Markers to mHealth Predictors., , and . Mobile Health - Sensors, Analytic Methods, and Applications, Springer, (2017)Linear Fitted-Q Iteration with Multiple Reward Functions., , and . ICAPS, AAAI, (2013)Translating Behavioral Theory into Technological Interventions: Case Study of an mHealth App to Increase Self-reporting of Substance-Use Related Data., , , , , , , , , and 4 other author(s). CoRR, (2020)Budgeted Learning for Developing Personalized Treatment., , and . ICMLA, page 7-14. IEEE, (2014)Assessing the Impact of Context Inference Error and Partial Observability on RL Methods for Just-In-Time Adaptive Interventions., , , and . UAI, volume 216 of Proceedings of Machine Learning Research, page 1047-1057. PMLR, (2023)Towards Optimizing Human-Centric Objectives in AI-Assisted Decision-Making With Offline Reinforcement Learning., , , , and . CoRR, (2024)Statistical Inference with M-Estimators on Adaptively Collected Data., , and . NeurIPS, page 7460-7471. (2021)Active exploration by searching for experiments that falsify the computed control policy., , , and . ADPRL, page 40-47. IEEE, (2011)ReBandit: Random Effects Based Online RL Algorithm for Reducing Cannabis Use., , , , , , , and . IJCAI, page 7278-7286. ijcai.org, (2024)iSurvive: An Interpretable, Event-time Prediction Model for mHealth., , , , , , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 970-979. PMLR, (2017)