Preprints

• Cai, Z., Fan, Y., Gao, L. (2025) Knockoffs inference under privacy constraints.

• Kanrar, R. 🎒, Jiang, F., Cai, Z. (2025) Model-free change-point detection using modern classifiers. Minor revision, Journal of Machine Learning Research.

• Xia, X. 🎒, Zhang, L., Cai, Z. (2025) Differentially private sliced inverse regression: minimax optimality and algorithm. Minor revision, Journal of the American Statistical Association.

• Cai, Z., Li, S., Xia, X. 🎒, Zhang, L. (2025) Private estimation and inference in high-dimensional regression with FDR control. R & R, Journal of Machine Learning Research.

Selected Publications

• Gao, Y., Zhang, Z., Cai, Z., Zhu, X., Zou, T., and Wang, H. (2024) Penalized sparse covariance regression with high dimensional covariates, Journal of Business & Economic Statistics.

• Awan, J., Cai, Z. (2024) One step to efficient synthetic data, Statistica Sinica.

• Xia, X. 🎒, Cai, Z. (2023) Adaptive false discovery rate control with privacy guarantee, Journal of Machine Learning Research.

• Cai, Z., Lei, J., Roeder, K. (2023) Asymptotic distribution-free independence test for high dimension data, Journal of the American Statistical Association. Python code

• Du, J., Cai, Z., Roeder, K. (2022) Robust probabilistic modeling for single-cell multimodal mosaic integration and imputation via scVAEIT, Proceedings of the National Academy of Sciences. Python package

• Cai, Z., Li, C., Wen, J., Yang, S. (2022) Asset splitting algorithm for ultrahigh dimensional portfolio selection and its theoretical property, Journal of Econometrics.

• Cai, Z., Lei, J., Roeder, K. (2022) Model-free prediction test with application to genomics data, Proceedings of the National Academy of Sciences.

• Cai, Z., Zhang, Y., Li, R. (2022) A distribution-free conditional independence test with application to causal discovery, Journal of Machine Learning Research. R package

• Tong, Z., Cai, Z., Yang, S., Li, R. (2022) Model-free conditional feature screening with FDR control, Journal of the American Statistical Association.

• Cai, Z., Xi, D., Zhu, X., Li, R. (2022) Causal discoveries for high dimensional mixed data, Statistics in Medicine. R code

• Zhu, X., Cai, Z., Ma, Y. (2021) Network functional autoregression model, Journal of the American Statistical Association. R code

• Cai, Z., Li, R., Zhu, L. (2020) Online sufficient dimension reduction through sliced inverse regression, Journal of Machine Learning Research, 21(10):1−25.

Note: 🎒 indicates student authors under my supervision.