Publications:

1. An approximate control variates approach to multifidelity distribution estimation (with B. Kramer, D. Lee, A. Narayan and Y. Xu), SIAM/ASA Journal on Uncertainty Quantification (2024). [arXiv]
   
2. Online Inference with Debiased Stochastic Gradient Descent (with L. Luo, Y. Lin and J. Huang), Biometrika (2024). [doi]
   
3. Online Inference in High-Dimensional Generalized Linear Models with Streaming Data (with L. Luo, Y. Lin and J. Huang). Electron. J. Stat. (2023). [doi]
   
4. A General Pairwise Comparison Model for Extremely Sparse Networks (with Y. Xu and K. Chen), J. Amer. Statist. Assoc. (2022). [doi]
   
5. Probabilistic Methods for Approximate Archetypal Analysis (with Y. Xu, B. Osting and D. Wang), Inf. Inference (2022). [doi]
   
6. Post-selection Inference of High-dimensional Logistic Regression under Case-control Design (with Y. Lin, J. Xie and N. Tang), J. Bus. Econ. Stat. (2022). [doi]
   
7. Asymptotic Theory of Sparse Bradley-Terry Model (with R. Ye, C. Tan and K. Chen), Ann. Appl. Probab. (2020). [doi]
   
8. Curiosity-Driven Recommendation Strategy for Adaptive Learning via Deep Reinforcement Learning (with K. Chen and C. Tan), Br. J. Math. Stat. Psychol. (2020). [doi]
   
9. Bivariate Gamma Model (with K. Chen and C. Tan), J. Multivar. Anal. (2020). [doi]
   
10. Adaptive Learning Recommendation Strategy Based on Deep Q-learning (with C. Tan, R. Ye and K. Chen), Appl. Psychol. Meas. (2020). [doi]

Preprint:

1. A unified analysis of likelihood-based estimators in the Plackett--Luce model (with Y. Xu). [arXiv]
   
2. Adaptive debiased SGD in high-dimensional GLMs with streaming data (with L. Luo, Y. Luo, Y. Lin and J. Huang). [arXiv]
   
3. Statistical ranking with dynamic covariates (with P. Dong, B. Jiang and Y. Xu). [arXiv]
   
4. Recursive Debiased Lasso for Streaming Data (with L. Luo, Y. Lin and J. Huang). [arXiv]