9 citations · 18 across the 16 of their papers we have counts for
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stat.ME2023★ 2 cited
Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators
Lin Liu, Rajarshi Mukherjee, James M. Robins
The class of doubly-robust (DR) functionals studied by Rotnitzky et al. (2021) is of central importance in economics and biostatistics. It strictly includes both (i) the class of m…
math.ST2023★ 1 cited
Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity
Lin Liu, Xinbo Wang, Yuhao Wang
Treatment effect estimation under unconfoundedness is a fundamental task in causal inference. In response to the challenge of analyzing high-dimensional datasets collected in subst…
math.ST2023
New -consistent, numerically stable higher-order influence function estimators
Lin Liu, Chang Li
Higher-Order Influence Functions (HOIFs) provide a unified theory for constructing rate-optimal estimators for a large class of low-dimensional (smooth) statistical functionals/par…