代表性论著
(1) Yinfeng Chen, Yuling Jiao, Rui Qiu and Zhou Yu (2024). Deep Nonlinear Sufficient Dimension Reduction. To appear in Annals of Statistics.
(2) Rui Qiu, Shuntuo Xu and Zhou Yu (2024). Neural Networks Meet Random Forests. Journal of the Royal Statistical Society Series B: Statistical Methodology. DOI: 10.1093/jrsssb/qkae038.
(3) Rui Qiu, Zhou Yu and Ruoqing Zhu (2024). Random Forest Weighted Local Fréchet Regression with Random Objects. Journal of Machine Learning Research, 25(107), 1-69.
(4) Jian Huang, Yuling Jiao, Xu Liao ,Jin Liu and Zhou Yu (2024) Deep Dimension Reduction for Supervised Representtion Learning. IEEE Transactions on Information Theory, 70(5), 3583-3598.
(5) Chao Ying and Zhou Yu (2022) Frechet sufficient Dimension Reduction for Random Objects. Biometrika, 109(4), 975-992.
(6) Kyongwon Kim, Bing Li, Zhou Yu and Lexin Li (2020) On Post Dimension Reduction Statistical Inference. Annals of Statistics, 48(3), 1567-1592.
(7) Kai Tan, Lei Shi and Zhou Yu (2020). Sparse SIR: Optimal Rates and Adaptive Estimation. Annals of Statistics, 48(1), 64-85.
(8) Zhou Yu, Yuexiao Dong and Jun Shao (2016). On Marginal Sliced Inverse Regression for Ultrahigh Dimensional Model-Free Feature Selection , Annals of Statistics, 44(6), 2594~2623.
(9) Zhou Yu,Yuexiao Dong and Li-Xing Zhu (2016). Trace Pursuit: A General Framework for Model-Free Variable Selection, Journal of the American Statistical Association, 2016, 111(514), 813~821.
(10) Zhou Yu, Liping Zhu, Heng Peng and Li-Xing Zhu (2013). Dimension Reduction and Predictor Selection in Semiparametric Models, Biometrika, 100(3), 641~654.
(11) Zhenghui Feng, Xuerong Meggie Wen, Zhou Yu and Li-Xing Zhu (2013). On Partial Sufficient Dimension Reduction With Applications to Partially Linear Multi-Index Models. Journal of the American Statistical Association, 108(501): 237~246.
