| Conditional Quantile Screening in Ultrahigh-Dimensional Heterogeneous Data Y Wu, G Yin Biometrika 102, 65-76, 2015 | 87 | 2015 |
| Additive–multiplicative rates model for recurrent events Y Liu, Y Wu, J Cai, H Zhou Lifetime Data Analysis 16 (3), 353-373, 2010 | 43 | 2010 |
| Correlation rank screening for ultrahigh-dimensional survival data J Zhang, Y Liu, Y Wu Computational Statistics & Data Analysis 108, 121-132, 2017 | 36 | 2017 |
| Smoothed and Corrected Score Approach to Censored Quantile Regression With Measurement Errors Y Wu, Y Ma, G Yin Journal of the American Statistical Association 110, 1670--1683, 2015 | 31 | 2015 |
| Statistical Inference for a Two‐Stage Outcome‐Dependent Sampling Design with a Continuous Outcome H Zhou, R Song, Y Wu, J Qin Biometrics 67 (1), 194-202, 2011 | 27 | 2011 |
| Cure Rate Quantile Regression for Censored Data With a Survival Fraction Y Wu, G Yin Journal of the American Statistical Association 108 (504), 1517-1531, 2013 | 26 | 2013 |
| Semiparametric inference for a 2-stage outcome-auxiliary-dependent sampling design with continuous outcome H Zhou, Y Wu, Y Liu, J Cai Biostatistics 12 (3), 521-534, 2011 | 19 | 2011 |
| Multivariate failure times regression with a continuous auxiliary covariate Y Liu, Y Wu, H Zhou Journal of Multivariate Analysis 101 (3), 679-691, 2010 | 19 | 2010 |
| Distributed quantile regression for massive heterogeneous data A Hu, Y Jiao, Y Liu, Y Shi, Y Wu Neurocomputing 448, 249-262, 2021 | 16 | 2021 |
| Censored cumulative residual independent screening for ultrahigh-dimensional survival data J Zhang, G Yin, Y Liu, Y Wu Lifetime Data Analysis 24 (2), 273-292, 2018 | 16 | 2018 |
| Functional Martingale Residual Process for High-Dimensional Cox Regression with Model Averaging B He, Y Liu, Y Wu, G Yin, X Zhao Journal of Machine Learning Research 21 (207), 1-37, 2020 | 12 | 2020 |
| An ADMM with continuation algorithm for non-convex SICA-penalized regression in high dimensions Y Shi, Y Wu, D Xu, Y Jiao Journal of Statistical Computation and Simulation 88 (9), 1826-1846, 2018 | 12 | 2018 |
| Sieve maximum likelihood estimation for a general class of accelerated hazards models with bundled parameters X Zhao, Y Wu, G Yin Bernoulli 23 (4B), 3385-3411, 2017 | 12 | 2017 |
| Restricted mean survival time for interval‐censored data C Zhang, Y Wu, G Yin Statistics in Medicine 39 (26), 3879-3895, 2020 | 10 | 2020 |
| Semiparametric additive intensity model with frailty for recurrent events YY Liu, YS Wu Acta Mathematica Sinica 27 (9), 1831-1842, 2011 | 10 | 2011 |
| Multiple imputation for cure rate quantile regression with censored data Y Wu, G Yin Biometrics 73, 94--103, 2017 | 8 | 2017 |
| TCB: A feature transformation method based central behavior for user interest prediction on mobile big data C Zhou, H Jiang, Y Chen, J Wu, J Zhou, Y Wu International Journal of Distributed Sensor Networks 12 (10), 1550147716671256, 2016 | 7 | 2016 |
| Exponential Regression for Censored Data With Outliers J Zhang, Y Liu, Y Wu Journal of Statistical Computation and Simulation 86, 431--442, 2016 | 6 | 2016 |
| Transfer learning with high-dimensional quantile regression J Huang, M Wang, Y Wu arXiv preprint arXiv:2211.14578, 2022 | 4 | 2022 |
| Semiparametric efficient estimation for additive hazards regression with case II interval-censored survival data B He, Y Liu, Y Wu, X Zhao Lifetime Data Analysis 26 (4), 708-730, 2020 | 4 | 2020 |
Guosheng YinUniversity of Hong KongVerified email at hku.hk
