Peng Liao

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Susan MurphyHarvard UniversityVerified email at g.harvard.edu
Predrag KlasnjaAssociate Professor, School of Information, University of MichiganVerified email at umich.edu
Walter DempseyUniversity of MichiganVerified email at umich.edu
Feiyun ZhuWalmart (Sam's Club) TechnologyVerified email at samsclub.com
Inbal Nahum-ShaniUniversity of Michigan Verified email at umich.edu
Junzhou HuangProfessor of Computer Science and Engineering at the University of Texas at ArlingtonVerified email at uta.edu
Santosh KumarLillian & Morrie Moss Chair of Excellence Professor, Computer Science, University of MemphisVerified email at memphis.edu
Ambuj Tewari | अम्बुज तिवारीProfessor, Statistics and EECS, University of MichiganVerified email at umich.edu
Sabina TomkinsAssistant Professor of Information, University of MichiganVerified email at umich.edu
Kristjan GreenewaldResearch Scientist, MIT-IBM Watson AI Lab, IBM ResearchVerified email at ibm.com
Runzhe WanAmazonVerified email at amazon.com
Syed Monowar HossainSoftware Engineer, FacebookVerified email at fb.com
Hillol SarkerSanofiVerified email at sanofi.com
Mustafa al'AbsiUniversity of Minnesota Medical School, DuluthVerified email at d.umn.edu
Zheng XuGoogle ResearchVerified email at google.com
Marianne MenictasPostdoctoral Researcher, Harvard UniversityVerified email at fas.harvard.edu
David E. ConroyThe Pennsylvania State UniversityVerified email at psu.edu
Samuel L BattalioNorthwestern UniversityVerified email at u.northwestern.edu
Bonnie SpringProfessor of Preventive Medicine, Psychology, & Psychiatry, Northwestern UniversityVerified email at northwestern.edu
Tianchen QianAssistant Professor of Statistics, University of California, IrvineVerified email at uci.edu

Peng Liao

Harvard University

Verified email at umich.edu - Homepage

Statistics Reinforcement Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Sample size calculations for micro‐randomized trials in mHealth P Liao, P Klasnja, A Tewari, SA Murphy Statistics in medicine 35 (12), 1944-1971, 2016	107	2016
Personalized heartsteps: A reinforcement learning algorithm for optimizing physical activity P Liao, K Greenewald, P Klasnja, S Murphy Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2020	77	2020
Randomised trials for the Fitbit generation W Dempsey, P Liao, P Klasnja, I Nahum‐Shani, SA Murphy Significance 12 (6), 20-23, 2015	47	2015
Off-policy estimation of long-term average outcomes with applications to mobile health P Liao, P Klasnja, S Murphy Journal of the American Statistical Association 116 (533), 382-391, 2021	39	2021
Batch policy learning in average reward markov decision processes P Liao, Z Qi, R Wan, P Klasnja, SA Murphy The Annals of Statistics 50 (6), 3364-3387, 2022	38	2022
Just-in-time but not too much: Determining treatment timing in mobile health P Liao, W Dempsey, H Sarker, SM Hossain, M Al'Absi, P Klasnja, ... Proceedings of the ACM on interactive, mobile, wearable and ubiquitous …, 2018	37	2018
The stratified micro-randomized trial design: sample size considerations for testing nested causal effects of time-varying treatments W Dempsey, P Liao, S Kumar, SA Murphy The annals of applied statistics 14 (2), 661, 2020	32	2020
Group-driven reinforcement learning for personalized mhealth intervention F Zhu, J Guo, Z Xu, P Liao, L Yang, J Huang Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018	22	2018
Sense2Stop: a micro-randomized trial using wearable sensors to optimize a just-in-time-adaptive stress management intervention for smoking relapse prevention SL Battalio, DE Conroy, W Dempsey, P Liao, M Menictas, S Murphy, ... Contemporary Clinical Trials 109, 106534, 2021	21	2021
Intelligentpooling: Practical thompson sampling for mhealth S Tomkins, P Liao, P Klasnja, S Murphy Machine learning 110 (9), 2685-2727, 2021	17	2021
Effective warm start for the online actor-critic reinforcement learning based mhealth intervention F Zhu, P Liao arXiv preprint arXiv:1704.04866, 2017	12	2017
Constructing just-in-time adaptive interventions P Liao, A Tewari, S Murphy Phd Section Proposal, 1-49, 2015	8	2015
Cohesion-based online actor-critic reinforcement learning for mhealth intervention F Zhu, P Liao, X Zhu, Y Yao, J Huang arXiv preprint arXiv:1703.10039, 2017	7	2017
Robust batch policy learning in markov decision processes Z Qi, P Liao arXiv preprint arXiv:2011.04185, 2020	5	2020
Rapidly personalizing mobile health treatment policies with limited data S Tomkins, P Liao, P Klasnja, S Yeung, S Murphy arXiv preprint arXiv:2002.09971, 2020	5	2020
Intelligent pooling in Thompson sampling for rapid personalization in mobile health S Tomkins, P Liao, S Yeung, P Klasnja, S Murphy	2	2019
Cohesion-driven Online Actor-Critic Reinforcement Learning for mHealth Intervention F Zhu, P Liao, X Zhu, J Yao, J Huang Proceedings of the 2018 ACM International Conference on Bioinformatics …, 2018	1	2018
Just-In-Time Adaptive Interventions: Experiment, Inference and Online Learning P Liao		2019

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