2 citations · 5 across the 6 of their papers we have counts for
6 papers
Evaluating time-varying treatment effects in hybrid SMART-MRT designs
Mengbing Li, Inbal Nahum-Shani, Walter Dempsey
Recently a new experimental approach, the hybrid experimental design (HED), was introduced to enable investigators to answer scientific questions about building behavioral interven…
ddtlcm: An R package for overcoming weak separation in Bayesian latent class analysis via tree-regularization
Mengbing Li, Bolin Wu, Briana Stephenson +1
Traditional applications of latent class models (LCMs) often focus on scenarios where a set of unobserved classes are well-defined and easily distinguishable. However, in numerous…
Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations
Mengbing Li, Briana Stephenson, Zhenke Wu
Dietary patterns synthesize multiple related diet components, which can be used by nutrition researchers to examine diet-disease relationships. Latent class models (LCMs) have been…
Doubly Inhomogeneous Reinforcement Learning
Liyuan Hu, Mengbing Li, Chengchun Shi +2
This paper studies reinforcement learning (RL) in doubly inhomogeneous environments under temporal non-stationarity and subject heterogeneity. In a number of applications, it is co…
Testing Stationarity and Change Point Detection in Reinforcement Learning
Mengbing Li, Chengchun Shi, Zhenke Wu +1
We consider offline reinforcement learning (RL) methods in possibly nonstationary environments. Many existing RL algorithms in the literature rely on the stationarity assumption th…
Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy
Zhenke Wu, Zehang Richard Li, Irena Chen +1
Determining causes of deaths (COD) occurred outside of civil registration and vital statistics systems is challenging. A technique called verbal autopsy (VA) is widely adopted to g…