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Inbal Nahum-Shani
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2020 – today
- 2024
- [c8]Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Lara N. Coughlin, Erin Bonar, Inbal Nahum-Shani, Maureen A. Walton, Susan A. Murphy:
ReBandit: Random Effects Based Online RL Algorithm for Reducing Cannabis Use. IJCAI 2024: 7278-7286 - [i13]Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Iris Yan, Finale Doshi-Velez, Susan A. Murphy:
Monitoring Fidelity of Online Reinforcement Learning Algorithms in Clinical Trials. CoRR abs/2402.17003 (2024) - [i12]Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Lara N. Coughlin, Erin Bonar, Inbal Nahum-Shani, Maureen A. Walton, Susan A. Murphy:
reBandit: Random Effects based Online RL algorithm for Reducing Cannabis Use. CoRR abs/2402.17739 (2024) - [i11]Anna L. Trella, Kelly W. Zhang, Stephanie M. Carpenter, David Elashoff, Zara M. Greer, Inbal Nahum-Shani, Dennis Ruenger, Vivek Shetty, Susan A. Murphy:
Oralytics Reinforcement Learning Algorithm. CoRR abs/2406.13127 (2024) - [i10]Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Lara N. Coughlin, Erin Bonar, Inbal Nahum-Shani, Maureen A. Walton, Susan A. Murphy:
MiWaves Reinforcement Learning Algorithm. CoRR abs/2408.15076 (2024) - [i9]Anna L. Trella, Kelly W. Zhang, Hinal Jajal, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy:
A Deployed Online Reinforcement Learning Algorithm In An Oral Health Clinical Trial. CoRR abs/2409.02069 (2024) - [i8]Anna L. Trella, Susobhan Ghosh, Erin Bonar, Lara N. Coughlin, Finale Doshi-Velez, Yongyi Guo, Pei-Yao Hung, Inbal Nahum-Shani, Vivek Shetty, Maureen A. Walton, Iris Yan, Kelly W. Zhang, Susan A. Murphy:
Effective Monitoring of Online Decision-Making Algorithms in Digital Intervention Implementation. CoRR abs/2409.10526 (2024) - 2023
- [j10]Linying Ji, Yanling Li, Lindsey N. Potter, Cho Lam, Inbal Nahum-Shani, David W. Wetter, Sy-Miin Chow
:
Multiple imputation of missing data in multilevel ecological momentary assessments: an example using smoking cessation study data. Frontiers Digit. Health 5 (2023) - [j9]Lindsey N. Potter, Inbal Nahum-Shani, David W. Wetter:
Editorial: Digital technology for tobacco control: Novel data collection, study designs, and interventions. Frontiers Digit. Health 5 (2023) - [j8]Michael Sobolev, Aditi Anand
Time-varying model of engagement with digital self reporting: Evidence from smoking cessation longitudinal studies. Frontiers Digit. Health 5 (2023) - [c7]Anna L. Trella, Kelly W. Zhang
Reward Design for an Online Reinforcement Learning Algorithm Supporting Oral Self-Care. AAAI 2023: 15724-15730 - [i7]Shuangning Li, Lluis Salvat Niell, Sung Won Choi, Inbal Nahum-Shani, Guy Shani, Susan A. Murphy:
Dyadic Reinforcement Learning. CoRR abs/2308.07843 (2023) - 2022
- [j7]Anna L. Trella
Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines. Algorithms 15(8): 255 (2022) - [j6]Inbal Nahum-Shani, John J. Dziak
MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions. Frontiers Digit. Health 4: 798025 (2022) - [j5]Lara N. Coughlin, Erin Bonar, Maureen A. Walton, Anne C. Fernandez, Isabelle Duguid, Inbal Nahum-Shani:
New Directions for Motivational Incentive Interventions for Smoking Cessation. Frontiers Digit. Health 4: 803301 (2022) - [j4]Md. Azim Ullah, Soujanya Chatterjee, Christopher P. Fagundes, Cho Lam, Inbal Nahum-Shani, James M. Rehg, David W. Wetter, Santosh Kumar:
mRisk: Continuous Risk Estimation for Smoking Lapse from Noisy Sensor Data with Incomplete and Positive-Only Labels. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6(3): 143:1-143:29 (2022) - [i6]Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy:
Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-implementation Guidelines. CoRR abs/2206.03944 (2022) - [i5]Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy:
Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care. CoRR abs/2208.07406 (2022) - 2021
- [j3]Sahar Hojjatinia
Dynamic models of stress-smoking responses based on high-frequency sensor data. npj Digit. Medicine 4 (2021) - [i4]Supriya Nagesh, Alexander Moreno, Stephanie M. Carpenter, Jamie Yap, Soujanya Chatterjee, Steven Lloyd Lizotte, Neng Wan, Santosh Kumar, Cho Lam, David W. Wetter, Inbal Nahum-Shani, James M. Rehg:
Transformers for prompt-level EMA non-response prediction. CoRR abs/2111.01193 (2021) - 2020
- [c6]Alexander Moreno, Zhenke Wu, Jamie Yap, Cho Lam, David W. Wetter, Inbal Nahum-Shani, Walter H. Dempsey, James M. Rehg:
A Robust Functional EM Algorithm for Incomplete Panel Count Data. NeurIPS 2020 - [i3]Alexander Moreno, Zhenke Wu, Jamie Yap, David W. Wetter, Cho Lam, Inbal Nahum-Shani, Walter H. Dempsey, James M. Rehg:
A Functional EM Algorithm for Panel Count Data with Missing Counts. CoRR abs/2003.01169 (2020) - [i2]Mashfiqui Rabbi, Meredith Philyaw-Kotov, Jinseok Li, Katherine Li, Bess Rothman, Lexa Giragosian, Maya Reyes, Hannah Gadway, Rebecca M. Cunningham, Erin Bonar, Inbal Nahum-Shani, Maureen A. Walton, Susan A. Murphy, Predrag V. Klasnja:
Translating Behavioral Theory into Technological Interventions: Case Study of an mHealth App to Increase Self-reporting of Substance-Use Related Data. CoRR abs/2003.13545 (2020) - [i1]Ashley E. Walton, Linda M. Collins, Predrag V. Klasnja, Inbal Nahum-Shani, Mashfiqui Rabbi, Maureen A. Walton, Susan A. Murphy:
The Micro-Randomized Trial for Developing Digital Interventions: Experimental Design Considerations. CoRR abs/2005.05880 (2020)
2010 – 2019
- 2019
- [c5]Blake Wagner III, Michael Barskey, Inbal Nahum-Shani, Sun Young Park:
ewrapper: Perceived Receptivity to Engagement Strategies in mHealth. CSCW Companion 2019: 398-402 - 2017
- [j2]Santosh Kumar, Gregory D. Abowd, William T. Abraham, Mustafa al'Absi, Duen Horng Chau
Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K). IEEE Pervasive Comput. 16(2): 18-22 (2017) - [c4]Mashfiqui Rabbi, Meredith Philyaw-Kotov, Jinseok Lee
SARA: a mobile app to engage users in health data collection. UbiComp/ISWC Adjunct 2017: 781-789 - [c3]Blake Wagner III, Elaine Liu, Steven D. Shaw
ewrapper: operationalizing engagement strategies in mHealth. UbiComp/ISWC Adjunct 2017: 790-798 - [p1]Hillol Sarker, Karen Hovsepian, Soujanya Chatterjee, Inbal Nahum-Shani, Susan A. Murphy, Bonnie Spring, Emre Ertin, Mustafa al'Absi, Motohiro Nakajima
From Markers to Interventions: The Case of Just-in-Time Stress Intervention. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 411-433 - 2016
- [c2]Hillol Sarker, Matthew Tyburski, Md. Mahbubur Rahman, Karen Hovsepian, Moushumi Sharmin, David H. Epstein, Kenzie L. Preston, C. Debra Furr-Holden, Adam Milam
Finding Significant Stress Episodes in a Discontinuous Time Series of Rapidly Varying Mobile Sensor Data. CHI 2016: 4489-4501 - 2015
- [j1]Santosh Kumar, Gregory D. Abowd, William T. Abraham, Mustafa al'Absi, J. Gayle Beck, Duen Horng Chau
Center of excellence for mobile sensor data-to-knowledge (MD2K). J. Am. Medical Informatics Assoc. 22(6): 1137-1142 (2015) - [c1]Moushumi Sharmin, Andrew Raij
Visualization of time-series sensor data to inform the design of just-in-time adaptive stress interventions. UbiComp 2015: 505-516
Coauthor Index
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