{"id":52,"date":"2020-10-15T21:11:50","date_gmt":"2020-10-15T20:11:50","guid":{"rendered":"http:\/\/blogs.kent.ac.uk\/statspengliu\/?page_id=52"},"modified":"2024-05-17T09:11:41","modified_gmt":"2024-05-17T08:11:41","slug":"publications","status":"publish","type":"page","link":"https:\/\/blogs.kent.ac.uk\/statspengliu\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"

Articles<\/h3>\n
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[1] Zhang, N., Liu, P.*<\/strong>, Kong, L., Jiang, B. and Huang, J. (2024). Functional Linear Quantile Regression on a Two-dimensional Domain. Bernoulli<\/em> 30<\/strong>(3): 1800-1824.<\/div>\n
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[2] Liu, P.*<\/strong>, Huang, Y., Chan, KCG. and Chen, Y. (2023). Semiparametric Trend Analysis for Stratified Recurrent Gap Times under Weak\u00a0Comparability Constraint. Statistics in Biosciences <\/em>15<\/strong>: 455-474.<\/div>\n
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[3] Ren, S.+, Wang, X., Liu, P.<\/strong> and Zhang, J. (2023). Bayesian Nonparametric Mixtures of Exponential Random Graph Models for Ensembles of Networks. Social Networks<\/em>\u00a074<\/strong>: 156-165.<\/div>\n
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[4] Liu, P.*<\/strong>, Chan, K. and Chen, Y. (2023). On a Simple Estimation of the Proportional Odds Model under Right Truncation. Lifetime Data Analysis <\/em>29<\/strong>: 537-554.<\/div>\n
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[5] Liu, M., Pietrosanu, M., Liu, P.<\/strong>, Jiang, B., Zhou, X. and Kong, L. (2022). Reproducing kernel-based functional linear expectile regression. The Canadian Journal of Statistics <\/i>50<\/strong>:<\/i> 241-266.<\/div>\n
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[6] Liu, P.<\/strong>, Song, S. and Zhou, Y. (2022). Semiparametric Additive Frailty Hazard Model for Clustered Failure Time Data. The Canadian Journal of Statistics <\/i>50<\/strong>: 549-571.<\/i><\/div>\n
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[7] Cheng, M., Huang, T., Liu, P.<\/strong> and Peng, H. (2018). Bias Reduction for Nonparametric and Semiparametric Regression Models. Statistica Sinica<\/i> 28<\/b>: 2749-2770. [Special Issue In Memory of Peter G. Hall]<\/div>\n
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[8] ZHANG, L., Liu, P.<\/strong> and ZHOU, Y. (2015). Smoothed Estimator of Quantile Residual Lifetime for Right Censored Data. Journal of Systems Science and Complexity <\/i>28<\/b>: 1374\u20131388.<\/div>\n
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[9] Liu, P.<\/strong>, Wang, Y. and Zhou, Y. (2014). Quantile residual lifetime with right-censored and length-biased data. <\/span>Annals of the Institute of Statistical Mathematics<\/i> 67<\/b>: 999-1028.<\/span><\/div>\n
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[10] Wang, Y., Liu, P.<\/strong> and Zhou, Y. (2014). Quantile residual lifetime for left-truncated and right-censored data. <\/span>Science in China Series A: Mathematics <\/i>58<\/b>: 1217\u20131234.<\/span><\/div>\n
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[11] Liu, Y.,<\/span> Liu, P.<\/span><\/strong>\u00a0and Zhou, Y. (2014). Smoothing Nonparametric Estimator <\/span>of Quantile Residual Lifetime under Compete Risk (in Chinese).<\/span> Acta Mathematicae <\/span>Applicatae Sinica (Chinese Series)<\/span><\/em>\u00a038<\/span><\/strong>:109-124.<\/span><\/div>\n
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Conference or workshop item<\/h3>\n
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[1]\u00a0Liu, P.*<\/strong>, Zhu, R., Liu, Y., Kong, L., Jiang, B., and Niu, D. (2023). Quantile Matrix Factorization: an Optimal Algorithm via Smooth Minimization. SIAM International Conference on Data Mining (SDM 2023). Accepted. (Top conference in Data Mining)<\/div>\n
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[2] Wang, Y., Pan, B., Tu, W., Liu, P.<\/strong>, Jiang, B., Gao, C.,\u00a0 Lu, W., Jui, S., and Kong, L. (2022). Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability. In: 36th AAAI Conference on Artificial Intelligence (AAAI-22). (Acceptance rate: 15%, A* conference in CORE2020 ranking, top conference in Artificial Intelligence)<\/div>\n
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[3] Tu, W., Liu, P.<\/strong>, Liu, Y., Li, G., Jiang, B., Kong, L., Yao, H., and Jiu, S. (2021). Nonsmooth Low-rank Matrix Recovery: Methodology, Theory and Algorithm. In: Future Technologies Conference (FTC) 2021.<\/div>\n
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[4] Liu, P.<\/strong>, 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<\/i>. IEEE, pp. 568-577.\u00a0 (Acceptance rate: 9.08%, A* conference in CORE2020 ranking)<\/div>\n
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[5] Hu, Y., Liu, P.<\/strong>, 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<\/em>. (A* conference in CORE2020 ranking, top conference in Computer Science)<\/div>\n<\/div>\n<\/div>\n
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Forthcoming<\/h3>\n
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[1] Wang, Y., Pan, B., Tu, W., Liu, P.<\/strong>, Jiang, B., Lu, W., Jui, S., and Kong, L. (2021). Convergence Analysis of the Stochastic Krasnosel’skii-Mann Algorithm. Submitted.<\/p>\n<\/div>\n

[2] Liu, P.*<\/strong>, Huang, Y., Chan, K., and Chen, Y. (2020). Semiparametric Trend Analysis for Stratified Recurrent Gap Times under Weak Comparability Constraint. Submitted.<\/div>\n<\/div>\n<\/div>\n
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[3] Liu, P.*<\/strong> (2020). Statistical Inference on the Monotonic Index Model Based on Monotone Rank Estimate. Submitted.<\/div>\n<\/div>\n<\/div>\n
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*: Corresponding author. +: Student supervised<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Articles [1] Zhang, N., Liu, P.*, Kong, L., Jiang, B. and Huang, J. (2024). Functional Linear Quantile Regression on a Two-dimensional Domain. Bernoulli 30(3): 1800-1824.…<\/p>\n

Continue readingPublications<\/span><\/a><\/div>\n","protected":false},"author":64025,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/blogs.kent.ac.uk\/statspengliu\/wp-json\/wp\/v2\/pages\/52"}],"collection":[{"href":"https:\/\/blogs.kent.ac.uk\/statspengliu\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/blogs.kent.ac.uk\/statspengliu\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.kent.ac.uk\/statspengliu\/wp-json\/wp\/v2\/users\/64025"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.kent.ac.uk\/statspengliu\/wp-json\/wp\/v2\/comments?post=52"}],"version-history":[{"count":30,"href":"https:\/\/blogs.kent.ac.uk\/statspengliu\/wp-json\/wp\/v2\/pages\/52\/revisions"}],"predecessor-version":[{"id":311,"href":"https:\/\/blogs.kent.ac.uk\/statspengliu\/wp-json\/wp\/v2\/pages\/52\/revisions\/311"}],"wp:attachment":[{"href":"https:\/\/blogs.kent.ac.uk\/statspengliu\/wp-json\/wp\/v2\/media?parent=52"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}