1. Pan, R., Chang, X., Zhu, X., and Wang, H. (2022) Link prediction via latent space logistic regression, Statistics and Its Interface, 15(3): 267-282.
2. Wu, S., Huang,D., and Wang, H. Network gradient descent algorithm for decentralized federated learning, Journal of Business and Economic Statistics, To appear.
3. Gao, Y., Liu, W., Wang, H., Wang, X., Yan, Y., and Zhang, R., A review of distributed statistical inference, Statistical Theory and Related Fields, To appear.
4. Zhu, X., Li, F., and Wang, H. Least-square approximation for a distributed system, Journal of Computational and Graphical Statistics, To appear.
5. Zhao, J., Liu, X., Wang, H. and Leng, C.,(2021) Dimension reduction for covariates in network data, Biometrika, To appear.
6. Zhu, X., Pan, R., Wu, S., and Wang, H. Feature Screening for Massive Data Analysis by Subsampling, Journal of Business & Economic Statistics, To appear.
7. Zhang, R., Zhou, J., Lan, W., and Wang, H. A Case Study on the Shareholder Network Effect of Stock Market Data: A SARMA Approach, Science China Mathematics, To appear.
8. Pan, R., Ren, T., Guo, B., Li, F., Li, G., and Wang, H. A Note on Distributed Quantile Regression by Pilot Sampling and One-Step Updating, Journal of Business and Economic Statistics, To appear.
9. Ma, Y., Guo, S., and Wang, H. Sparse spatio-temporal autoregressions by profiling and bagging, Journal of Econometrics, To appear.
10. Zhou, J., Liu, J, Wang, F., and Wang, H. Autoregression model with spatial dependence and missing data, Journal of Business & Economic Statistics, To appear.