{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T13:46:01Z","timestamp":1780407961009,"version":"3.54.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2024,4,10]],"date-time":"2024-04-10T00:00:00Z","timestamp":1712707200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,4,10]],"date-time":"2024-04-10T00:00:00Z","timestamp":1712707200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DMS2023528"],"award-info":[{"award-number":["DMS2023528"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["R01HL125440"],"award-info":[{"award-number":["R01HL125440"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["1U01CA229445"],"award-info":[{"award-number":["1U01CA229445"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000026","name":"National Institute on Drug Abuse","doi-asserted-by":"publisher","award":["P50DA054039"],"award-info":[{"award-number":["P50DA054039"]}],"id":[{"id":"10.13039\/100000026","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000070","name":"National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["P41EB028242"],"award-info":[{"award-number":["P41EB028242"]}],"id":[{"id":"10.13039\/100000070","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["U01CA229437"],"award-info":[{"award-number":["U01CA229437"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000072","name":"National Institute of Dental and Craniofacial Research","doi-asserted-by":"publisher","award":["UH3DE028723"],"award-info":[{"award-number":["UH3DE028723"]}],"id":[{"id":"10.13039\/100000072","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000072","name":"National Institute of Dental and Craniofacial Research","doi-asserted-by":"publisher","award":["DGE1745303"],"award-info":[{"award-number":["DGE1745303"]}],"id":[{"id":"10.13039\/100000072","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["T32GM135117"],"award-info":[{"award-number":["T32GM135117"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DMS2022448"],"award-info":[{"award-number":["DMS2022448"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001445","name":"DSO National Laboratories - Singapore","doi-asserted-by":"publisher","award":["CO21070"],"award-info":[{"award-number":["CO21070"]}],"id":[{"id":"10.13039\/501100001445","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001445","name":"DSO National Laboratories - Singapore","doi-asserted-by":"publisher","award":["CBET21112085"],"award-info":[{"award-number":["CBET21112085"]}],"id":[{"id":"10.13039\/501100001445","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1007\/s10994-024-06526-x","type":"journal-article","created":{"date-parts":[[2024,4,10]],"date-time":"2024-04-10T15:01:27Z","timestamp":1712761287000},"page":"3961-3997","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling"],"prefix":"10.1007","volume":"113","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3654-4141","authenticated-orcid":false,"given":"Susobhan","family":"Ghosh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raphael","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Prasidh","family":"Chhabria","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raaz","family":"Dwivedi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Predrag","family":"Klasnja","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Liao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kelly","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susan","family":"Murphy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,10]]},"reference":[{"issue":"12","key":"6526_CR1","doi-asserted-by":"publisher","first-page":"0277295","DOI":"10.1371\/journal.pone.0277295","volume":"17","author":"N Albers","year":"2022","unstructured":"Albers, N., Neerincx, M. A., & Brinkman, W.-P. (2022). Addressing people\u2019s current and future states in a reinforcement learning algorithm for persuading to quit smoking and to be physically active. PLoS ONE, 17(12), 0277295.","journal-title":"PLoS ONE"},{"issue":"2\u20133","key":"6526_CR2","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1023\/A:1013689704352","volume":"47","author":"P Auer","year":"2002","unstructured":"Auer, P., Cesa-Bianchi, N., & Fischer, P. (2002). Finite-time analysis of the multiarmed bandit problem. Machine Learning, 47(2\u20133), 235\u2013256. https:\/\/doi.org\/10.1023\/A:1013689704352","journal-title":"Machine Learning"},{"issue":"1\u20132","key":"6526_CR3","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1007\/s10998-010-3055-6","volume":"61","author":"P Auer","year":"2010","unstructured":"Auer, P., & Ortner, R. (2010). UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem. Periodica Mathematica Hungarica, 61(1\u20132), 55\u201365. https:\/\/doi.org\/10.1007\/s10998-010-3055-6","journal-title":"Periodica Mathematica Hungarica"},{"key":"6526_CR4","first-page":"679","volume":"6","author":"R Bellman","year":"1957","unstructured":"Bellman, R. (1957). A Markovian decision process. Journal of Mathematics and Mechanics, 6, 679\u2013684.","journal-title":"Journal of Mathematics and Mechanics"},{"key":"6526_CR5","unstructured":"Bibaut, A., Chambaz, A., Dimakopoulou, M., Kallus, N., & Laan, M. (2021). Post-contextual-bandit inference."},{"key":"6526_CR6","unstructured":"Boger, J., Poupart, P., Hoey, J., Boutilier, C., Fernie, G. R., & Mihailidis, A. (2005). A decision-theoretic approach to task assistance for persons with dementia. In: Kaelbling, L.P., Saffiotti, A. (eds.), IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30\u2013August 5, 2005, pp. 1293\u20131299. Professional Book Center, UK. http:\/\/ijcai.org\/Proceedings\/05\/Papers\/1186.pdf."},{"issue":"523","key":"6526_CR7","doi-asserted-by":"publisher","first-page":"1112","DOI":"10.1080\/01621459.2017.1305274","volume":"113","author":"A Boruvka","year":"2018","unstructured":"Boruvka, A., Almirall, D., Witkiewitz, K., & Murphy, S. A. (2018). Assessing time-varying causal effect moderation in mobile health. Journal of the American Statistical Association, 113(523), 1112\u20131121.","journal-title":"Journal of the American Statistical Association"},{"key":"6526_CR8","first-page":"499","volume":"2","author":"O Bousquet","year":"2002","unstructured":"Bousquet, O., & Elisseeff, A. (2002). Stability and generalization. The Journal of Machine Learning Research, 2, 499\u2013526.","journal-title":"The Journal of Machine Learning Research"},{"key":"6526_CR9","doi-asserted-by":"publisher","DOI":"10.2307\/1390754","author":"A Buja","year":"1996","unstructured":"Buja, A., Cook, D., & Swayne, D. F. (1996). Interactive high-dimensional data visualization. Journal of Computational and Graphical Statistics. https:\/\/doi.org\/10.2307\/1390754","journal-title":"Journal of Computational and Graphical Statistics"},{"issue":"6","key":"6526_CR10","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1111\/j.1740-9713.2015.00863.x","volume":"12","author":"W Dempsey","year":"2015","unstructured":"Dempsey, W., Liao, P., Klasnja, P., Nahum-Shani, I., & Murphy, S. A. (2015). Randomised trials for the fitbit generation. Significance, 12(6), 20\u201323. https:\/\/doi.org\/10.1111\/j.1740-9713.2015.00863.x","journal-title":"Significance"},{"key":"6526_CR11","doi-asserted-by":"publisher","first-page":"655","DOI":"10.1111\/rssb.12124","volume":"78","author":"P Ding","year":"2016","unstructured":"Ding, P., Feller, A., & Miratrix, L. (2016). Randomization inference for treatment effect variation. Journal of the Royal Statistical Society: Series B: Statistical Methodology, 78, 655\u2013671.","journal-title":"Journal of the Royal Statistical Society: Series B: Statistical Methodology"},{"key":"6526_CR12","unstructured":"Dwaracherla, V., Lu, X., Ibrahimi, M., Osband, I., Wen, Z., & Roy, B. V. (2020). Hypermodels for exploration. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net, Addis Ababa. https:\/\/openreview.net\/forum?id=ryx6WgStPB."},{"key":"6526_CR13","unstructured":"Dwivedi, R., Tian, K., Tomkins, S., Klasnja, P., Murphy, S., & Shah, D. (2022). Counterfactual inference for sequential experiments."},{"key":"6526_CR14","doi-asserted-by":"publisher","DOI":"10.1177\/2158244019851675","author":"D Eckles","year":"2019","unstructured":"Eckles, D., & Kaptein, M. (2019). Bootstrap thompson sampling and sequential decision problems in the behavioral sciences. SAGE Open. https:\/\/doi.org\/10.1177\/2158244019851675","journal-title":"SAGE Open"},{"key":"6526_CR15","doi-asserted-by":"publisher","DOI":"10.1201\/9780429246593","author":"B Efron","year":"1994","unstructured":"Efron, B., & Tibshirani, R. J. (1994). An introduction to the bootstrap. Monographs on Statistics and applied Probability. https:\/\/doi.org\/10.1201\/9780429246593","journal-title":"Monographs on Statistics and applied Probability"},{"key":"6526_CR16","doi-asserted-by":"publisher","unstructured":"Elmachtoub, A. N., McNellis, R., Oh, S., & Petrik, M. (2017). A practical method for solving contextual bandit problems using decision trees. https:\/\/doi.org\/10.48550\/arxiv.1706.04687.","DOI":"10.48550\/arxiv.1706.04687"},{"key":"6526_CR17","volume-title":"The design of experiments","author":"RA Fisher","year":"1935","unstructured":"Fisher, R. A. (1935). The design of experiments. Oliver and Boyd."},{"key":"6526_CR18","doi-asserted-by":"publisher","first-page":"107029","DOI":"10.1016\/j.cct.2022.107029","volume":"124","author":"EM Forman","year":"2023","unstructured":"Forman, E. M., Berry, M. P., Butryn, M. L., Hagerman, C. J., Huang, Z., Juarascio, A. S., LaFata, E. M., Onta\u00f1\u00f3n, S., Tilford, J. M., & Zhang, F. (2023). Using artificial intelligence to optimize delivery of weight loss treatment: Protocol for an efficacy and cost-effectiveness trial. Contemporary Clinical Trials, 124, 107029.","journal-title":"Contemporary Clinical Trials"},{"issue":"2","key":"6526_CR19","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1007\/s10865-018-9964-1","volume":"42","author":"EM Forman","year":"2019","unstructured":"Forman, E. M., Kerrigan, S. G., Butryn, M. L., Juarascio, A. S., Manasse, S. M., Onta\u00f1\u00f3n, S., Dallal, D. H., Crochiere, R. J., & Moskow, D. (2019). Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss? Journal of Behavioral Medicine, 42(2), 276\u2013290.","journal-title":"Journal of Behavioral Medicine"},{"key":"6526_CR20","doi-asserted-by":"publisher","DOI":"10.1198\/106186004X11435","author":"A Gelman","year":"2004","unstructured":"Gelman, A. (2004). Exploratory data analysis for complex models. Journal of Computational and Graphical Statistics. https:\/\/doi.org\/10.1198\/106186004X11435","journal-title":"Journal of Computational and Graphical Statistics"},{"key":"6526_CR21","volume-title":"Resampling methods","author":"PI Good","year":"2006","unstructured":"Good, P. I. (2006). Resampling methods. Springer."},{"key":"6526_CR22","unstructured":"Hadad, V., Hirshberg, D. A., Zhan, R., Wager, S., & Athey, S. (2019). Confidence intervals for policy evaluation in adaptive experiments."},{"key":"6526_CR23","doi-asserted-by":"crossref","unstructured":"Hanna, J. P., Stone, P., & Niekum, S. (2017). Bootstrapping with models: Confidence intervals for off-policy evaluation. In Proceedings of the international joint conference on autonomous agents and multiagent systems, AAMAS, vol. 1.","DOI":"10.1609\/aaai.v31i1.11123"},{"key":"6526_CR24","unstructured":"Hao, B., Abbasi-Yadkori, Y., Wen, Z., & Cheng, G. (2019). Bootstrapping upper confidence bound. In Advances in neural information processing systems, vol. 32."},{"key":"6526_CR25","unstructured":"Hao, B., Ji, X., Duan, Y., Lu, H., Szepesvari, C., & Wang, M. (2021). Bootstrapping fitted q-evaluation for off-policy inference. In Proceedings of the 38th international conference on machine learning, vol. 139."},{"key":"6526_CR26","unstructured":"Hoey, J., Poupart, P., Boutilier, C., & Mihailidis, A.(2005). POMDP models for assistive technology. In: Bickmore, T.W. (ed.), Caring machines: AI in Eldercare, Papers from the 2005 AAAI Fall Symposium, Arlington, Virginia, USA, November 4-6, 2005. AAAI Technical Report, vol. FS-05-02, pp. 51\u201358. AAAI Press, Washington, D.C. https:\/\/www.aaai.org\/Library\/Symposia\/Fall\/2005\/fs05-02-009.php."},{"key":"6526_CR27","doi-asserted-by":"publisher","unstructured":"Liang, D., Charlin, L., McInerney, J., & Blei, D. M. (2016). Modeling user exposure in recommendation. In Proceedings of the 25th international conference on World Wide Web. WWW \u201916, pp. 951\u2013961. International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE. https:\/\/doi.org\/10.1145\/2872427.2883090.","DOI":"10.1145\/2872427.2883090"},{"issue":"1","key":"6526_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3381007","volume":"4","author":"P Liao","year":"2020","unstructured":"Liao, P., Greenewald, K., Klasnja, P., & Murphy, S. (2020). Personalized heartsteps: A reinforcement learning algorithm for optimizing physical activity. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(1), 1\u201322.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"6526_CR29","doi-asserted-by":"publisher","DOI":"10.1145\/3381007","author":"P Liao","year":"2020","unstructured":"Liao, P., Greenewald, K., Klasnja, P., & Murphy, S. (2020). Personalized heartsteps: A reinforcement learning algorithm for optimizing physical activity. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. https:\/\/doi.org\/10.1145\/3381007","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"6526_CR30","doi-asserted-by":"publisher","first-page":"100064","DOI":"10.1016\/j.ibmed.2022.100064","volume":"6","author":"JD Piette","year":"2022","unstructured":"Piette, J. D., Newman, S., Krein, S. L., Marinec, N., Chen, J., Williams, D. A., Edmond, S. N., Driscoll, M., LaChappelle, K. M., Maly, M., et al. (2022). Artificial intelligence (AI) to improve chronic pain care: Evidence of AI learning. Intelligence-Based Medicine, 6, 100064.","journal-title":"Intelligence-Based Medicine"},{"issue":"3","key":"6526_CR31","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1093\/biomet\/asaa070","volume":"108","author":"T Qian","year":"2021","unstructured":"Qian, T., Yoo, H., Klasnja, P., Almirall, D., & Murphy, S. A. (2021). Estimating time-varying causal excursion effects in mobile health with binary outcomes. Biometrika, 108(3), 507\u2013527.","journal-title":"Biometrika"},{"key":"6526_CR32","unstructured":"Ramprasad, P., Li, Y., Yang, Z., Wang, Z., Sun, W. W., & Cheng, G. (2021). Online bootstrap inference for policy evaluation in reinforcement learning."},{"key":"6526_CR33","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-3692-2","volume-title":"Observational studies","author":"P Rosenbaum","year":"2002","unstructured":"Rosenbaum, P. (2002). Observational studies. Springer."},{"key":"6526_CR34","unstructured":"Russo, D., & Roy, B. V. (2014). Learning to optimize via information-directed sampling. In Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D., Weinberger, K.Q. (eds.), Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada, pp. 1583\u20131591. https:\/\/proceedings.neurips.cc\/paper\/2014\/hash\/301ad0e3bd5cb1627a2044908a42fdc2-Abstract.html."},{"key":"6526_CR35","doi-asserted-by":"crossref","unstructured":"Russo, D. J., Van\u00a0Roy, B., Kazerouni, A., Osband, I., & Wen, Z. et al (2018). A tutorial on thompson sampling. Foundations and Trends\u00ae in Machine Learning11(1):1\u201396.","DOI":"10.1561\/2200000070"},{"issue":"1","key":"6526_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2200000070","volume":"11","author":"D Russo","year":"2018","unstructured":"Russo, D., Roy, B. V., Kazerouni, A., Osband, I., & Wen, Z. (2018). A tutorial on thompson sampling. Foundations and Trends in Machine Learning, 11(1), 1\u201396. https:\/\/doi.org\/10.1561\/2200000070","journal-title":"Foundations and Trends in Machine Learning"},{"key":"6526_CR37","doi-asserted-by":"publisher","DOI":"10.1109\/tnn.1998.712192","author":"RS Sutton","year":"1998","unstructured":"Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning: An introduction. IEEE Transactions on Neural Networks. https:\/\/doi.org\/10.1109\/tnn.1998.712192","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"3\/4","key":"6526_CR38","doi-asserted-by":"publisher","first-page":"285","DOI":"10.2307\/2332286","volume":"25","author":"WR Thompson","year":"1933","unstructured":"Thompson, W. R. (1933). On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika, 25(3\/4), 285\u2013294.","journal-title":"Biometrika"},{"key":"6526_CR39","unstructured":"Tomkins, S., Liao, P., Yeung, S., Klasnja, P., & Murphy, S. (2019). Intelligent pooling in Thompson sampling for rapid personalization in mobile health."},{"key":"6526_CR40","volume-title":"Exploratory data analysis","author":"JW Tukey","year":"1977","unstructured":"Tukey, J. W. (1977). Exploratory data analysis (Vol. 2). Reading."},{"key":"6526_CR41","volume-title":"Theory of pattern recognition","author":"V Vapnik","year":"1974","unstructured":"Vapnik, V., & Chervonenkis, A. (1974). Theory of pattern recognition. Nauka."},{"key":"6526_CR42","unstructured":"Wang, C.-H., Yu, Y., Hao, B., & Cheng, G. (2020). Residual bootstrap exploration for bandit algorithms."},{"key":"6526_CR43","unstructured":"White, M., & White, A. (2010). Interval estimation for reinforcement-learning algorithms in continuous-state domains. In Advances in neural information processing systems 23: 24th annual conference on neural information processing systems 2010, NIPS 2010."},{"key":"6526_CR44","unstructured":"Yang, J., Eckles, D., Dhillon, P., & Aral, S. (2020). Targeting for long-term outcomes. arXiv:2010.15835."},{"issue":"10","key":"6526_CR45","doi-asserted-by":"publisher","first-page":"338","DOI":"10.2196\/jmir.7994","volume":"19","author":"E Yom-Tov","year":"2017","unstructured":"Yom-Tov, E., Feraru, G., Kozdoba, M., Mannor, S., Tennenholtz, M., & Hochberg, I. (2017). Encouraging physical activity in patients with diabetes: Intervention using a reinforcement learning system. Journal of Medical Internet Research, 19(10), 338.","journal-title":"Journal of Medical Internet Research"},{"key":"6526_CR46","doi-asserted-by":"publisher","DOI":"10.2196\/JMIR.7994","author":"E Yom-Tov","year":"2017","unstructured":"Yom-Tov, E., Feraru, G., Kozdoba, M., Mannor, S., Tennenholtz, M., & Hochberg, I. (2017). Encouraging physical activity in patients with diabetes: Intervention using a reinforcement learning system. Journal of Medical Internet Research. https:\/\/doi.org\/10.2196\/JMIR.7994","journal-title":"Journal of Medical Internet Research"},{"key":"6526_CR47","unstructured":"Zhang, K. W., Janson, L., & Murphy, S. A. (2020). Inference for batched bandits."},{"key":"6526_CR48","unstructured":"Zhang, K. W., Janson, L., & Murphy, S. A. (2023). Statistical inference after adaptive sampling for longitudinal data."},{"key":"6526_CR49","unstructured":"Zhou, M., Mintz, Y., Fukuoka, Y., Goldberg, K., Flowers, E., Kaminsky, P. M., Castillejo, A., & Aswani, A. (2018). Personalizing mobile fitness apps using reinforcement learning. In: Said, A., Komatsu, T. (eds.), Joint Proceedings of the ACM IUI 2018 Workshops Co-located with the 23rd ACM Conference on Intelligent User Interfaces (ACM IUI 2018), Tokyo, Japan, March 11. CEUR Workshop Proceedings, vol. 2068. CEUR-WS.org, Tokyo (2018). https:\/\/ceur-ws.org\/Vol-2068\/humanize7.pdf."}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-024-06526-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10994-024-06526-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-024-06526-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T18:06:20Z","timestamp":1764266780000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10994-024-06526-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,10]]},"references-count":49,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2024,7]]}},"alternative-id":["6526"],"URL":"https:\/\/doi.org\/10.1007\/s10994-024-06526-x","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,10]]},"assertion":[{"value":"17 April 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 August 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 February 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 April 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"KWZ worked as a summer intern at Apple. The other authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"We adhere to the policies outlined in\n                      \n                      .","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"The reported study was approved by the Kaiser Permanente Washington Institutional Review Board (IRB 1257484-16). All participants completed a written informed consent to take part in the study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Adhering to the IRB and consent forms, individual level data that could be used for identification are not released.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}