Sai Li. Debiasing the debiased Lasso with bootstrap. Electronic Journal of Statistics. 14(1): 2298-2337,2020.
Sai Li, T. Tony Cai, and Hongzhe Li. Inference for high-dimensional linear mixed-effects models: A quasi-likelihood approach. Journal of the American Statistical Association. 117(540): 1835-1846, 2022.
Sai Li, T. Tony Cai, and Hongzhe Li. Estimation and Inference with Proxy Data and its Genetic Applications. Statistica Sinica (accepted). 2024.
Sai Li and Linjun Zhang. Multi-dimensional domain generalization with low-rank structures. Submitted. 2023.
Sai Li, T. Tony Cai, and Hongzhe Li. Transfer learning for high-dimensional linear regression: Prediction, estimation, and minimax optimality. Journal of the Royal Statistical Society Series B. 84: 149–173, 2022.
Sai Li, T. Tony Cai, and Hongzhe Li. Transfer learning in large-scale graphical models with false discovery rate control. Journal of the American Statistical Association.118(543), 2171-2183, 2023.
Sai Li, Tianxi Cai, and Rui Duan. Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approach. Annals of Applied Statistics. 17(4), 2970-2992, 2023.
Sai Li, Linjun Zhang, T. Tony Cai, and Hongzhe Li. Estimation and inference in high-dimensional generalized linear models with knowledge transfer. Journal of the American Statistical Association. 119(546), 1274-1285, 2024.
Sai Li and Ting Ye. A Focusing Framework for Testing Bi-Directional Causal Effects with GWAS Summary Data. Journal of the Royal Statistical Society: Series B (accepted). 2024.
Ziya Xu and Sai Li. Leveraging Local Distributions in Mendelian Randomization: Uncertain Opinions are Invalid. Statistica Sinica (accepted). 2024. (with my student)
Wei Li, Rui Duan, and Sai Li. Discovery and inference of possibly bi-directional causal relationships with invalid instrumental variables. Submitted. 2024.
Sai Li and Zijian Guo. Causal inference for nonlinear outcomes with possibly invalid instrumentalvariables. Technical report. 2020.
Sai Li. Mendelian Randomization when many instruments are invalid: hierarchical empirical Bayes estimation. Technical report. 2017.
Zhanrui Cai, Sai Li, Xintao Xia, and Linjun Zhang. Differentially Private Estimation and Inference in High-Dimensional Regression with FDR Control. (submitted). 2024. (alphabetical order)
Jianqiao Wang, Sai Li, and Hongzhe Li. A unified approach to robust inference for genetic covariance. Journal of the American Statistical Association (accepted). 2023.
Sai Li, Yisha Yao, and Cun-Hui Zhang. Comment: A Scale-Free Approach for False Discovery Rate Control in Generalized Linear Models. Journal of the American Statistical Association(accepted). 2023.
Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, and Chelsea Finn. Improving out-of-distribution robustness via selective augmentation. International Conference of Machine Learning. 2022.
Sai Li, Ritwik Mitra, and Cun-Hui Zhang. Comment: An adaptive resampling test for detecting the presence of significant predictors. Journal of the American Statistical Association. 110(512): 1455-1456. 2016.