1 code implementation • 31 May 2023 • Shumin Ma, Zhiri Yuan, Qi Wu, Yiyan Huang, Xixu Hu, Cheuk Hang Leung, Dongdong Wang, Zhixiang Huang
This paper proposes a new domain adaptation approach in which one can measure the differences in the internal dependence structure separately from those in the marginals.
no code implementations • 5 Sep 2022 • Yiyan Huang, Cheuk Hang Leung, Shumin Ma, Qi Wu, Dongdong Wang, Zhixiang Huang
In this paper, we propose a moderately-balanced representation learning (MBRL) framework based on recent covariates balanced representation learning methods and orthogonal machine learning theory.
no code implementations • 5 Sep 2022 • Yiyan Huang, Cheuk Hang Leung, Xing Yan, Qi Wu, Shumin Ma, Zhiri Yuan, Dongdong Wang, Zhixiang Huang
Theoretically, the RCL estimators i) are as consistent and doubly robust as the DML estimators, and ii) can get rid of the error-compounding issue.
no code implementations • 3 Jun 2019 • Qi Wu, Shumin Ma, Cheuk Hang Leung, Wei Liu, Nanbo Peng
Without the boundedness constraint, the CCO problem is shown to perform uniformly better than the DRO problem, irrespective of the radius of the ambiguity set, the choice of the divergence measure, or the tail heaviness of the center distribution.