1 citations · 3 across the 6 of their papers we have counts for
6 papers
Enhancing Treatment Effect Estimation: A Model Robust Approach Integrating Randomized Experiments and External Controls using the Double Penalty Integration Estimator
Yuwen Cheng, Lili Wu, Shu Yang
Randomized experiments (REs) are the cornerstone for treatment effect evaluation. However, due to practical considerations, REs may encounter difficulty recruiting sufficient patie…
Anytime-valid off-policy inference for contextual bandits
Ian Waudby-Smith, Lili Wu, Aaditya Ramdas +2
Contextual bandit algorithms are ubiquitous tools for active sequential experimentation in healthcare and the tech industry. They involve online learning algorithms that adaptively…
Transfer learning of individualized treatment rules from experimental to real-world data
Lili Wu, Shu Yang
Individualized treatment effect lies at the heart of precision medicine. Interpretable individualized treatment rules (ITRs) are desirable for clinicians or policymakers due to the…
Estimating spatially varying health effects of wildland fire smoke using mobile health data
Lili Wu, Chenyin Gao, Shu Yang +2
Wildland fire smoke exposures are an increasing threat to public health, and thus there is a growing need for studying the effects of protective behaviors on reducing health outcom…
Parameterized Exploration
Jesse Clifton, Lili Wu, Eric Laber
We introduce Parameterized Exploration (PE), a simple family of methods for model-based tuning of the exploration schedule in sequential decision problems. Unlike common heuristics…
Multivariate Density Estimation with Missing Data
Zhen Li, Lili Wu, Weilian Zhou +1
Multivariate density estimation is a popular technique in statistics with wide applications including regression models allowing for heteroskedasticity in conditional variances. Th…