8 citations · 8 across the 2 of their papers we have counts for
2 papers
stat.ME2022
Distributed Design for Causal Inferences on Big Observational Data
Yumin Zhang, Arman Sabbaghi
A fundamental issue in causal inference for Big Observational Data is confounding due to covariate imbalances between treatment groups. This can be addressed by designing the data…
cs.LG2020★ 8 cited
Feature Selection Methods for Uplift Modeling and Heterogeneous Treatment Effect
Zhenyu Zhao, Yumin Zhang, Totte Harinen +1
Uplift modeling is a causal learning technique that estimates subgroup-level treatment effects. It is commonly used in industry and elsewhere for tasks such as targeting ads. In a…