7 papers
On the convolution theorem for directionally pathwise differentiable functionals
Shuoxun Xu
The classical semiparametric convolution theorem characterizes the limiting distributions of regular estimators of pathwise differentiable parameters. We extend this analysis to di…
Structure-based Transfer Learning
Ho Yi Alexis Ho, Xinzhou Guo, Shuoxun Xu
Transfer learning improves estimation in a target study using information from related sources. Classical transfer learning is typically data-based, requiring access to the source…
Evaluation of Combination Therapy amid Patient-Level Heterogeneity
Lingjie Wei, Xinzhou Guo, Shuoxun Xu
Combination therapy, a treatment approach that involves two or more monotherapies, is widely considered to enhance therapeutic efficacy across different medical conditions. It was…
Stein-Encoder: A White-Box Supervised Encoder via Stein Identities in Multi-Modal Studies
Jiarui Zhang, Shuoxun Xu, Jiasheng Shi +1
In multi-modal biomedical research, integrating high-dimensional genomic data with clinical baselines is essential for precision medicine. However, standard deep neural network app…
In-Sample Evaluation of Subgroups Identified by Generic Machine Learning
Shuoxun Xu, Xinzhou Guo
When a subgroup is identified from the data, it must be evaluated in a replicable way. The usual in-sample approach, which evaluates the post-hoc identified subgroup as predefined,…
Robust Learning of Heterogeneous Dynamic Systems
Shuoxun Xu, Zijian Guo, Brooke R. Staveland +2
Ordinary differential equations (ODEs) provide a powerful framework for modeling dynamic systems arising in a wide range of scientific domains. However, most existing ODE methods f…
Optimal Inference of the Mean Outcome under Optimal Treatment Regime
Shuoxun Xu, Xinzhou Guo
When an optimal treatment regime (OTR) is considered, we need to evaluate the OTR in a valid and efficient way. The classical inference applied to the mean outcome under OTR, assum…