Variance reduction combining pre-experiment and in-experiment data Zhexiao Lin and Pablo Crespo, 2024. Extended abstract accepted at 2024 CODE@MIT.
Supervised deep learning with gene annotation for cell classification Zhexiao Lin and Wei Sun, 2024.
On regression-adjusted imputation estimators of the average treatment effect Zhexiao Lin and Fang Han, 2022.
Limit theorems of Chatterjee's rank correlation Zhexiao Lin and Fang Han, 2022. “R&R” at Annals of Statistics.
On Rosenbaum's rank-based matching estimator Matias D. Cattaneo, Fang Han, and Zhexiao Lin (alphabetical order). Biometrika, to appear, 2024+.
On the failure of the bootstrap for Chatterjee's rank correlation Zhexiao Lin and Fang Han. Biometrika, 111(3): 1063-1070, 2024.
Estimation based on nearest neighbor matching: from density ratio to average treatment effect Zhexiao Lin, Peng Ding, and Fang Han. Econometrica, 91(6): 2187-2217, 2023.
On boosting the power of Chatterjee's rank correlation Zhexiao Lin and Fang Han. Biometrika, 110(2): 283-299, 2023.
On the sequence evaluation based on stochastic processes Tianhao Zhang*, Zhexiao Lin*, Zhecheng Sheng*, Chen Jiang* and Dongyeop Kang (*=equal contributions), 2024.
RoVista: Measuring and Understanding the Route Origin Validation (ROV) in RPKI Weitong Li, Zhexiao Lin, Mohammad Ishtiaq Ashiq Khan, Emile Aben, Romain Fontugne, Amreesh Phokeer, and Taejoong Chung. Proceedings of the 2023 ACM on Internet Measurement Conference, 73-88, 2023.
Topic-aware chatbot using Recurrent Neural Networks and Nonnegative Matrix Factorization Y. Guo, N. Hanoian, Z. Lin, N. Liskij, H. Lyu, D. Needell, J. Qu, H. Sojico, Y. Wang, Z. Xiong, and Z. Zou, 2019.