6 papers
When to repeat a biomarker test? Decomposing sources of variation from conditionally repeated measurements
Supun Manathunga, Mart P. Janssen, Yu Luo +2
Repeating an imperfect biomarker test based on an initial result can introduce bias and influence misclassification risk. For example, in some blood donation settings, blood donors…
Boosting CVaR Policy Optimization with Quantile Gradients
Yudong Luo, Erick Delage
Optimizing Conditional Value-at-risk (CVaR) using policy gradient (a.k.a CVaR-PG) faces significant challenges of sample inefficiency. This inefficiency stems from the fact that it…
An Infinite BART model
Marco Battiston, Yu Luo
Bayesian additive regression trees (BART) are popular Bayesian ensemble models used in regression and classification analysis. Under this modeling framework, the regression functio…
A longitudinal Bayesian framework for estimating causal dose-response relationships
Yu Luo, Kuan Liu, Ramandeep Singh +1
Existing causal methods for time-varying exposure and time-varying confounding focus on estimating the average causal effect of a time-varying binary treatment on an end-of-study o…
A scalable Bayesian double machine learning framework, with application to racial disproportionality assessment
Yu Luo, Vanessa McNealis, Yijing Li
Racial disproportionality in stop and search practices elicits substantial concerns about its societal and behavioral impacts. In London, Black individuals are about four times mor…
Bayesian inference for the Markov-modulated Poisson process with an outcome process
Yu Luo, Chris Sherlock
In medical research, understanding changes in outcome measurements is crucial for inferring shifts in health conditions. However, traditional methods often struggle with large, irr…