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作者：Chen, Haoyu; Lu, Wenbin; Song, Rui
作者单位：North Carolina State University
摘要：Online decision making problem requires us to make a sequence of decisions based on incremental information. Common solutions often need to learn a reward model of different actions given the contextual information and then maximize the long-term reward. It is meaningful to know if the posited model is reasonable and how the model performs in the asymptotic sense. We study this problem under the setup of the contextual bandit framework with a linear reward model. The epsilon-greedy policy is a...
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作者：Guo, Wenchuan; Zhou, Xiao-Hua; Ma, Shujie
作者单位：University of California System; University of California Riverside; Bristol-Myers Squibb; Peking University; Peking University
摘要：With a large number of baseline covariates, we propose a new semiparametric modeling strategy for heterogeneous treatment effect estimation and individualized treatment selection, which are two major goals in personalized medicine. We achieve the first goal through estimating a covariate-specific treatment effect (CSTE) curve modeled as an unknown function of a weighted linear combination of all baseline covariates. The weight or the coefficient for each covariate is estimated by fitting a spa...
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作者：Cui, Yifan; Tchetgen, Eric Tchetgen
作者单位：University of Pennsylvania
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作者：Liao, Peng; Klasnja, Predrag; Murphy, Susan
作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; Harvard University
摘要：Due to the recent advancements in wearables and sensing technology, health scientists are increasingly developing mobile health (mHealth) interventions. In mHealth interventions, mobile devices are used to deliver treatment to individuals as they go about their daily lives. These treatments are generally designed to impact a near time, proximal outcome such as stress or physical activity. The mHealth intervention policies, often called just-in-time adaptive interventions, are decision rules th...
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作者：Han, Sukjin
作者单位：University of Bristol
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作者：Glennie, R.; Buckland, S. T.; Langrock, R.; Gerrodette, T.; Ballance, L. T.; Chivers, S. J.; Scott, M. D.
作者单位：University of St Andrews; University of Bielefeld; National Oceanic Atmospheric Admin (NOAA) - USA
摘要：Distance sampling is a popular statistical method to estimate the density of wild animal populations. Conventional distance sampling represents animals as fixed points in space that are detected with an unknown probability that depends on the distance between the observer and the animal. Animal movement can cause substantial bias in density estimation. Methods to correct for responsive animal movement exist, but none account for nonresponsive movement independent of the observer. Here, an expl...
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作者：Lin, Kevin Z.; Liu, Han; Roeder, Kathryn
作者单位：Carnegie Mellon University; Northwestern University
摘要：Risk for autism can be influenced by genetic mutations in hundreds of genes. Based on findings showing that genes with highly correlated gene expressions are functionally interrelated, guilt by association methods such as DAWN have been developed to identify these autism risk genes. Previous research analyzes the BrainSpan dataset, which contains gene expression of brain tissues from varying regions and developmental periods. Since the spatiotemporal properties of brain tissue are known to aff...
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作者：Liu, Lin; Shahn, Zach; Robins, James M.; Rotnitzky, Andrea
作者单位：Shanghai Jiao Tong University; Shanghai Jiao Tong University; International Business Machines (IBM); IBM USA; Harvard University; Universidad Torcuato Di Tella; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
摘要：We derive new estimators of an optimal joint testing and treatment regime under the no direct effect (NDE) assumption that a given laboratory, diagnostic, or screening test has no effect on a patient's clinical outcomes except through the effect of the test results on the choice of treatment. We model the optimal joint strategy with an optimal structural nested mean model (opt-SNMM). The proposed estimators are more efficient than previous estimators of the parameters of an opt-SNMM because th...
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作者：Nemeth, Christopher; Fearnhead, Paul
作者单位：Lancaster University
摘要：Markov chain Monte Carlo (MCMC) algorithms are generally regarded as the gold standard technique for Bayesian inference. They are theoretically well-understood and conceptually simple to apply in practice. The drawback of MCMC is that performing exact inference generally requires all of the data to be processed at each iteration of the algorithm. For large datasets, the computational cost of MCMC can be prohibitive, which has led to recent developments in scalable Monte Carlo algorithms that h...
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作者：Xia, Lucy; Zhao, Richard; Wu, Yanhui; Tong, Xin
作者单位：Hong Kong University of Science & Technology; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; University of Hong Kong; University of Southern California; University of Southern California
摘要：This article addresses the challenges in classifying textual data obtained from open online platforms, which are vulnerable to distortion. Most existing classification methods minimize the overall classification error and may yield an undesirably large Type I error (relevant textual messages are classified as irrelevant), particularly when available data exhibit an asymmetry between relevant and irrelevant information. Data distortion exacerbates this situation and often leads to fallacious pr...
