4 papers
Moderately-Balanced Representation Learning for Treatment Effects with Orthogonality Information
Yiyan Huang, Cheuk Hang Leung, Shumin Ma +3
Estimating the average treatment effect (ATE) from observational data is challenging due to selection bias. Existing works mainly tackle this challenge in two ways. Some researcher…
Robust Causal Learning for the Estimation of Average Treatment Effects
Yiyan Huang, Cheuk Hang Leung, Xing Yan +5
Many practical decision-making problems in economics and healthcare seek to estimate the average treatment effect (ATE) from observational data. The Double/Debiased Machine Learnin…
The Causal Learning of Retail Delinquency
Yiyan Huang, Cheuk Hang Leung, Xing Yan +4
This paper focuses on the expected difference in borrower's repayment when there is a change in the lender's credit decisions. Classical estimators overlook the confounding effects…
Understanding Distributional Ambiguity via Non-robust Chance Constraint
Qi Wu, Shumin Ma, Cheuk Hang Leung +2
This paper provides a non-robust interpretation of the distributionally robust optimization (DRO) problem by relating the distributional uncertainties to the chance probabilities.…