Journal Articles

Zhang, F, Chen, X, Liu, P, Fan, C (2024) Weighted expectile regression neural networks for right censored data, Statistics in Medicine, ISSN: 0277-6715. DOI: 10.1002/sim.10221.

Zhang, N, Liu, P, Kong, L, Jiang, B, Huang, JZ (2024) Functional linear quantile regression on a two-dimensional domain, Bernoulli, 30(3), pp.1800-1824, ISSN: 1350-7265. DOI: 10.3150/23-bej1653.

Liu, P, Huang, Y, Chan, KCG, Chen, YQ (2023) Semiparametric Trend Analysis for Stratified Recurrent Gap Times Under Weak Comparability Constraint, Statistics in Biosciences, 15(2), pp.455-474, ISSN: 1867-1764. DOI: 10.1007/s12561-023-09376-8.

Ren, S, Wang, X, Liu, P, Zhang, J (2023) Bayesian nonparametric mixtures of Exponential Random Graph Models for ensembles of networks, Social Networks, 74, pp.156-165, ISSN: 0378-8733. DOI: 10.1016/j.socnet.2023.03.005.

Liu, P, Chan, KCG, Chen, YQ (2023) On a simple estimation of the proportional odds model under right truncation, Lifetime Data Analysis, 29(3), pp.537-554, ISSN: 1380-7870. DOI: 10.1007/s10985-022-09584-2.

Liu, P, Song, S, Zhou, Y (2022) Semiparametric additive frailty hazard model for clustered failure time data, Canadian Journal of Statistics, 50(2), pp.549-571, ISSN: 0319-5724. DOI: 10.1002/cjs.11647.

Liu, M, Pietrosanu, M, Liu, P, Jiang, B, Zhou, X, Kong, L (2022) Reproducing kernel‐based functional linear expectile regression, Canadian Journal of Statistics, 50(1), pp.241-266, ISSN: 0319-5724. DOI: 10.1002/cjs.11679.

Cheng, M-Y, Huang, T, Liu, P, Peng, H (2018) Bias Reduction for Nonparametric and Semiparametric Regression Models, Statistica Sinica, ISSN: 1017-0405. DOI: 10.5705/ss.202017.0058.

Zhang, L, Liu, P, Zhou, Y (2015) Smoothed estimator of quantile residual lifetime for right censored data, Journal of Systems Science and Complexity, 28(6), pp.1374-1388, ISSN: 1009-6124. DOI: 10.1007/s11424-015-3067-7.

Liu, P, Wang, Y, Zhou, Y (2015) Quantile residual lifetime with right-censored and length-biased data, Annals of the Institute of Statistical Mathematics, 67(5), pp.999-1028, ISSN: 0020-3157. DOI: 10.1007/s10463-014-0482-9.

Wang, Y, Liu, P, Zhou, Y (2015) Quantile residual lifetime for left-truncated and right-censored data, Science China Mathematics, 58(6), pp.1217-1234, ISSN: 1674-7283. DOI: 10.1007/s11425-014-4868-1.

Conferences

Liu, P, Kong, L, Niu, D, Liu, Y, Zhu, R, Jiang, B (2023) Optimal Smooth Approximation for Quantile Matrix Factorization. In 2023 SIAM International Conference on Data Mining (SDM), Minneapolis, Minnesota, U.S.

Liu, P, Wang, Y, Pan, B, Tu, W, Jiang, B, Gao, C, Lu, W, Jui, S, Kong, L (2022) Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability. In The Thirty-Sixth AAAI Conference on Artificial Intelligence, Online.

Liu, P, Tu, W, Li, G, Liu, Y, Jiang, B, Kong, L, Yao, H, Jui, S (2021) Nonsmooth low-rank matrix recovery: methodology, theory and algorithm. In Future Technologies Conference 2021, Online. DOI: 10.1007/978-3-030-89906-6_54.

Hu, Y, Liu, P, Ge, K, Kong, L, Jiang, B, Niu, D (2020) Learning Privately over Distributed Features: An ADMM Sharing Approach. In NeurIPS-20 Workshop on Scalability, Privacy, and Security in Federated Learning, Online.

Tu, W, Liu, P, Zhao, J, Liu, Y, Kong, L, Li, G, Jiang, B, Tian, G, Yao, H (2019) M-estimation in Low-Rank Matrix Factorization: A General Framework. In 2019 IEEE International Conference on Data Mining (ICDM), pp.568-577, DOI: 10.1109/icdm.2019.00067.