Journal Articles

Nair, A and Liu, P (2026) When metadata betrays the mission: learning to defend UAV swarms with adaptive privacy, Ad Hoc Networks, ISSN: 1570-8705.

Liu, Y, Li, R, Duan, R, Liu, P (2025) Does digital transformation enhance the economic vitality of Chinese enterprises?: evidence from A-share listed companies, Future Business Journal, 11(1), 168, ISSN: 2314-7202. DOI: 10.1186/s43093-025-00594-8.

Li, J, Green, G, Carr, SJA, Liu, P, Zhang, J (2025) Bayesian inference general procedures for a single-subject test study, Neuroscience Informatics, 5(2), 100195, ISSN: 2772-5286. DOI: 10.1016/j.neuri.2025.100195.

Zhang, F, Chen, X, Liu, P, Fan, C (2024) Weighted expectile regression neural networks for right censored data, Statistics in Medicine, 43(27), pp.5100-5114, 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, M, Pietrosanu, M, Liu, P, Jiang, B, Zhou, X, Kong, L (2021) Reproducing kernel‐based functional linear expectile regression, Canadian Journal of Statistics, 50(1), pp.241-266, ISSN: 0319-5724. DOI: 10.1002/cjs.11679.

Liu, P, Song, S, Zhou, Y (2021) 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.

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

Talha, A, Liu, P, Souradyuti, P (2026) Usefulness of quantile-aware diffusion modeling for highly imbalanced tabular data. In Computational Data and Social Networks 15th International Conference, CSoNet 2026, Ho Chi Minh City, Vietnam.

Liu, P, Liu, Y, Zhu, R, Kong, L, Jiang, B, Niu, D (2023) Optimal smooth approximation for Quantile Matrix Factorization. In Shekhar, S, Zhou, Z-H, Chiang, Y-Y, Stiglic, G (ed) 2023 SIAM International Conference on Data Mining (SDM); Proceedings of the 2023 SIAM International Conference on Data Mining (SDM), Minneapolis, Minnesota, U.S, pp.595-603, ISBN: 9781611977653. DOI: 10.1137/1.9781611977653.ch67.

Wang, Y, Pan, B, Tu, W, Liu, P, 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, pp.3859-3867, ISBN: 9781577358763. DOI: 10.1609/aaai.v36i4.20301.

Tu, W, Liu, P, Liu, Y, Li, G, Jiang, B, Kong, L, Yao, H, Jui, S (2021) Nonsmooth low-rank matrix recovery: methodology, theory and algorithm. In Arai, K (ed) Future Technologies Conference 2021; Proceedings of the Future Technologies Conference (FTC) 2021, Online,ISBN: 9783030899066. DOI: 10.1007/978-3-030-89906-6_54.

Hu, Y, Liu, P, Kong, L, Niu, D (2020) Learning privately over distributed features: an ADMM sharing approach. In NeurIPS-20 Workshop on Scalability, Privacy, and Security in Federated Learning; NeurIPS-20 International Workshop on Scalability, Privacy, and Security in Federated Learning (Spicy FL), 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.

Presentations

Ljaz, H, Adukia, V, Menon, D, Ali, H, Liu, P (2026) Risk Factors For Developing Acute Kidney Injury In Patients Undergoing Single Stage Hip And Knee Revision Arthroplasty For Aseptic Loosening.

Datasets

Li, J, Green, G, JA Carr, S, Liu, P, Zhang, J (2025) Supplementary information for "Bayesian inference general procedures for a single-subject test study", DOI: 10.17028/rd.lboro.29266982.