Publications

Note: + Co-first authorship; * Corresponding authorship.

  1. Xie, J.+, Shi, E.+, Sang, P., Shang, Z., Jiang, B., and Kong, L.* (2025). Scalable inference in functional linear regression with streaming data. The Annals of Statistics, accepted.
  2. Zhang, Z., Chen, Z., Liu, Q., Xie, J., and Zhu, H. (2025). Sampling-guided heterogeneous graph neural network with temporal smoothing for scalable longitudinal data imputation. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), acceptance rate: 18.4%.
  3. Zhang, Q.+ , Li, T.+, Feng, X., Yan, X., and Xie, J.* (2025). Online differential private conformal prediction for uncertainty quantification. Forty-Second International Conference on Machine Learning (ICML), acceptance rate: 26.9%. [pdf]
  4. Xie, J., Yan, X., Jiang, B., and Kong, L.* (2025). Statistical inference for smoothed quantile regression with streaming data. Journal of Econometrics, 249, 105924.
  5. Qin, C., Xie, J., Li, T., and Bai, Y.* (2024). An adaptive transfer learning framework for functional classification. Journal of the American Statistical Association, 120, 1201–1213.
  6. Han, D.+, Xie, J.+, Liu, J.*, Sun, L., Huang, J., Jiang, B. and Kong, L. (2024). Inference on high-dimensional single-index models with streaming data. Journal of Machine Learning Research, 25, 1-68.
  7. Shi, E., Xie, J., Hu, S., Sun, K., Dai, H., Jiang, B., Kong, L., and Li, L.* (2024). Tracking full posterior in online Bayesian classification learning: A particle filter approach. Journal of Nonparametric Statistics, accepted.
  8. Dong, W., Xu, C., Xie, J., and Tang, N.* (2024). Tuning-free sparse clustering via alternating hard-thresholding. Journal of Multivariate Analysis, 203, 105330.
  9. Kong, L., Luo, X., Xie, J., Zhu, L., and Zhu, H.* (2024). A functional nonlinear mixed effects modeling framework for longitudinal functional responses. Electronic Journal of Statistics, 18, 1355-1393.
  10. Xie, J.+, Ding, X.+, Jiang, B., Yan, X. and Kong, L.* (2024). High dimensional model averaging for quantile regression. The Canadian Journal of Statistics, 52, 618-635.
  11. Yan, X., Xie, J., Tu, W., Jiang, B., and Kong, L.* (2023). Scalable inference for individual treatment effect. Statistics and Its Interface, accepted.
  12. Lin Y.+, Xie, J.+, Han, R.+, and Tang, N.* (2023). Post-selection inference of high-dimensional logistic regression under case-control design. Journal of Business & Economic Statistics, 41, 624-635.
  13. Yan, X., Wang, H., Zhou, Y., Yan, J., Wang, Y., Xie, J.*, Yang, S.*, Zeng, Z.*, and Chen, X.* (2022). Heterogeneous logistic regression for estimation of subgroup effects on hypertension. Journal of Biopharmaceutical Statistics, 32, 969-985.
  14. Hu, S.*, Al-Ani, J. A., Hughes, K. D., Denier, N., Konnikov, A., Ding, L., Xie, J., Yang, H., Tarafdar, M., Jiang, B., Kong, L. and Dai, H. (2022). Balancing gender bias in job advertisements with Text-level bias mitigation. Frontiers in Big Data, accepted.
  15. Ding, L., Yu, D., Xie, J., Guo, W., Hu, S., Liu, M., Kong, L.*, Dai, H., Bao, Y and Jiang, B. (2022). Word embeddings via causal inference: gender bias reducing and semantic information preserving. Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), acceptance rate: 15.0%.
  16. Tang, W., Xie, J., Lin, Y. and Tang, N.* (2022). Quantile correlation-based variable selection. Journal of Business & Economic Statistics, 40, 1081-1093.
  17. Ding, X., Xie, J.* and Yan, X.* (2021). Model averaging for composite quantile regressions with covariates missing at random. Journal of Statistical Computation and Simulation, 91, 2249-2275.
  18. Yan, X., Wang, H., Wang, W., Xie, J.*, Ren, Y.*, and Wang, X.* (2021). Optimal model averaging forecasting in high-dimensional survival analysis. International Journal of Forecasting, 37, 1147-1155.
  19. Xie, J., Yan, X. and Tang, N.* (2021). A model-averaging method for high-dimensional regression with missing responses at random. Statistica Sinica, 31, 1005-1026.
  20. Xie, J., Lin, Y.*, Yan, X. and Tang, N. (2020). Category-adaptive variable screening for ultra-high dimensional heterogeneous categorical data. Journal of the American Statistical Association, 115, 747-760.
  21. Xie, J., Hao, M., Liu, W. and Lin, Y.* (2020). Fused variable screening for massive imbalanced data. Computational Statistics & Data Analysis, 141, 94-108.
  22. Li, X., Tang, N.*, Xie, J. and Yan, X. (2020). A nonparametric feature screening method for ultrahigh-dimensional missing data. Computational Statistics & Data Analysis, accepted.
  23. Yan, X., Tang, N.*, Xie, J., Ding, X. and Wang, Z. (2018). Fused mean-variance filter for feature screening. Computational Statistics & Data Analysis, 122, 18-32.