Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Guo, Yongyi"'
Autor:
Trella, Anna L., Ghosh, Susobhan, Bonar, Erin E., Coughlin, Lara, Doshi-Velez, Finale, Guo, Yongyi, Hung, Pei-Yao, Nahum-Shani, Inbal, Shetty, Vivek, Walton, Maureen, Yan, Iris, Zhang, Kelly W., Murphy, Susan A.
Online AI decision-making algorithms are increasingly used by digital interventions to dynamically personalize treatment to individuals. These algorithms determine, in real-time, the delivery of treatment based on accruing data. The objective of this
Externí odkaz:
http://arxiv.org/abs/2409.10526
Autor:
Ghosh, Susobhan, Guo, Yongyi, Hung, Pei-Yao, Coughlin, Lara, Bonar, Erin, Nahum-Shani, Inbal, Walton, Maureen, Murphy, Susan
The escalating prevalence of cannabis use poses a significant public health challenge globally. In the U.S., cannabis use is more prevalent among emerging adults (EAs) (ages 18-25) than any other age group, with legalization in the multiple states co
Externí odkaz:
http://arxiv.org/abs/2408.15076
Autor:
Ghosh, Susobhan, Guo, Yongyi, Hung, Pei-Yao, Coughlin, Lara, Bonar, Erin, Nahum-Shani, Inbal, Walton, Maureen, Murphy, Susan
The escalating prevalence of cannabis use, and associated cannabis-use disorder (CUD), poses a significant public health challenge globally. With a notably wide treatment gap, especially among emerging adults (EAs; ages 18-25), addressing cannabis us
Externí odkaz:
http://arxiv.org/abs/2402.17739
App-based N-of-1 trials offer a scalable experimental design for assessing the effects of health interventions at an individual level. Their practical success depends on the strong motivation of participants, which, in turn, translates into high adhe
Externí odkaz:
http://arxiv.org/abs/2309.07353
We consider the contextual bandit problem where at each time, the agent only has access to a noisy version of the context and the error variance (or an estimator of this variance). This setting is motivated by a wide range of applications where the t
Externí odkaz:
http://arxiv.org/abs/2307.13916
Autor:
Coughlin, Lara N., Campbell, Maya, Wheeler, Tiffany, Rodriguez, Chavez, Florimbio, Autumn Rae, Ghosh, Susobhan, Guo, Yongyi, Hung, Pei-Yao, Newman, Mark W., Pan, Huijie, Zhang, Kelly W., Zimmermann, Lauren, Bonar, Erin E., Walton, Maureen, Murphy, Susan, Nahum-Shani, Inbal
Publikováno v:
In Contemporary Clinical Trials October 2024 145
In this paper, we study the contextual dynamic pricing problem where the market value of a product is linear in its observed features plus some market noise. Products are sold one at a time, and only a binary response indicating success or failure of
Externí odkaz:
http://arxiv.org/abs/2109.06368
We consider the problem of variance reduction in randomized controlled trials, through the use of covariates correlated with the outcome but independent of the treatment. We propose a machine learning regression-adjusted treatment effect estimator, w
Externí odkaz:
http://arxiv.org/abs/2106.07263
Best subset selection (BSS) is widely known as the holy grail for high-dimensional variable selection. Nevertheless, the notorious NP-hardness of BSS substantially restricts its practical application and also discourages its theoretical development t
Externí odkaz:
http://arxiv.org/abs/2007.01478
Autor:
Chen, Yuexi, Xie, Chunjie, Yang, Shixuan, He, Ran, Guo, Yongyi, Guo, Zhao-Xia, Guo, Baohua, Qiu, Teng, Tuo, Xinlin
Publikováno v:
In Composites Science and Technology 29 September 2023 242