144 citations · 407 across the 41 of their papers we have counts for
5 papers · 1 filter
Sufficient Dimension Reduction for Average Causal Effect Estimation
Debo Cheng, Jiuyong Li, Lin Liu +1
Having a large number of covariates can have a negative impact on the quality of causal effect estimation since confounding adjustment becomes unreliable when the number of covaria…
A unified survey of treatment effect heterogeneity modeling and uplift modeling
Weijia Zhang, Jiuyong Li, Lin Liu
A central question in many fields of scientific research is to determine how an outcome would be affected by an action, or to measure the effect of an action (a.k.a treatment effec…
Local search for efficient causal effect estimation
Debo Cheng, Jiuyong Li, Lin Liu +3
Causal effect estimation from observational data is a challenging problem, especially with high dimensional data and in the presence of unobserved variables. The available data-dri…
Towards unique and unbiased causal effect estimation from data with hidden variables
Debo Cheng, Jiuyong Li, Lin Liu +3
Causal effect estimation from observational data is a crucial but challenging task. Currently, only a limited number of data-driven causal effect estimation methods are available.…
Identify treatment effect patterns for personalised decisions
Jiuyong Li, Lin Liu, Shisheng Zhang +3
In personalised decision making, evidence is required to determine whether an action (treatment) is suitable for an individual. Such evidence can be obtained by modelling treatment…