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[1] Liu, P., Song, S. and Zhou, Y. (2020). Semiparametric Additive Frailty Hazard Model for Clustered Failure Time Data. The Canadian Journal of Statistics (to appear).
[2] Cheng, M., Huang, T., Liu, P. and Peng, H. (2018). Bias Reduction for Nonparametric and Semiparametric Regression Models. Statistica Sinica 28: 2749-2770. [Special Issue In Memory of Peter G. Hall]
[3] ZHANG, L., Liu, P. and ZHOU, Y. (2015). Smoothed Estimator of Quantile Residual Lifetime for Right Censored Data. Journal of Systems Science and Complexity 28: 1374–1388.
[4] Liu, P., Wang, Y. and Zhou, Y. (2014). Quantile residual lifetime with right-censored and length-biased data. Annals of the Institute of Statistical Mathematics 67: 999-1028.
[5] Wang, Y., Liu, P. and Zhou, Y. (2014). Quantile residual lifetime for left-truncated and right-censored data. Science in China Series A: Mathematics 58: 1217–1234.

Conference or workshop item

[1] Liu, P., Tu, W., Zhao, J., Liu, Y., Kong, L., Li, G., Jiang, B., Tian, G. and Yao, H. (2020). M-estimation in Low-rank Matrix Factorization: a General Framework. In: 19th IEEE International Conference on Data Mining. IEEE, pp. 568-577.  (Acceptance rate: 9.08%, A* conference in CORE2020 ranking)
[2] Hu, Y., Liu, P., Ge, K., Kong, L., Jiang, B. and Niu D. (2020). Learning Privately over Distributed Features: An ADMM Sharing Approach. In: NeurIPS-20 Workshop on Scalability, Privacy, and Security in Federated Learning. (A* conference in CORE2020 ranking, top conference in Computer Science)


[1] Liu, P., Zhu, R., Liu, Y., Kong, L., Jiang, B., and Niu, D. (2021). Quantile Matrix Factorization: an Optimal Algorithm via Smooth Minimization. Submitted.
[2] Wang, Y., Pan, B., Tu, W., Liu, P., Jiang, B., Lu, W., Jui, S., and Kong, L. (2021). Convergence Analysis of the Stochastic Krasnosel’skii-Mann Algorithm. Submitted.
[3] Liu, P., Huang, Y., Chan, K., and Chen, Y. (2020). Semiparametric Trend Analysis for Stratified Recurrent Gap Times under Weak Comparability Constraint. Submitted.
[4] Liu, P. (2020). Statistical Inference on the Monotonic Index Model Based on Monotone Rank Estimate. Submitted.
[5] Tu, W., Liu, P., Liu, Y., Kong, L., Li, G., Jiang, B., Yao, H., and Jui, S. (2019). Nonsmooth low-rank matrix recovery: methodology, theory and algorithm. Submitted.
[6] Liu, P., Chan, K. and Chen, Y. (2019). On a Simple Estimation of the Proportional Odds Model under Right Truncation. Submitted.