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  • 郑泽敏
  • 教授
  • zhengzm@ustc.edu.cn
  • 统计与金融系
  • 概率与统计
English
  • Using machine learning to advance disparities research: Subgroup analyses of access to opioid treatment , Health Services Research , 2022 , 57: 411-421
  • Nonsparse Learning with Latent Variables , Operations Research , 2021 , 69(1): 346-359
  • Innovated interaction screening for high-dimensional nonlinear classification , Annals of Statistics , 2015 , 43(3): 1243-1272
  • High-dimensional thresholded regression and shrinkage effect , Journal of the Royal Statistical Society Series B-Statistical Methodology , 2014 , 76(3): 627-649
  • Discussion: A significance test for the Lasso , Annals of Statistics , 2014 , 42(2): 493-500
  • Sequential Scaled Sparse Factor Regression , Journal of Business & Economic Statistics , 2022 , 40(2): 595-604
  • Fast stagewise sparse factor regression , Journal of Machine Learning Research , 2022 , 23: 1-45
  • Scalable interpretable multi-response regression via SEED , Journal of Machine Learning Research , 2019 , 20: 1-34
  • The constrained Dantzig selector with enhanced consistency , Journal of Machine Learning Research , 2016 , 17: 1-22
  • Reproducible learning in large-scale graphical models , Journal of Multivariate Analysis , 2022 , 189104934
  • Partitioned approach for high-dimensional confidence intervals with large split sizes , Statistica Sinica , 2021 , 31: 1935-1959
  • Parallel integrative learning for large-scale multi-response regression with incomplete outcomes , Computational Statistics and Data Analysis , 2021 , 160107243
  • Scalable interpretable learning for multi-response error-in-variables regression , Journal of Multivariate Analysis , 2020 , 179: 1-14
  • Uniform joint screening for ultra-high dimensional graphical models , Journal of Multivariate Analysis , 2020 , 179: 1-13
  • Balanced estimation for high-dimensional measurement error models , Computational Statistics and Data Analysis , 2018 , 126: 78-91
  • Reproducible feature selection in high-dimensional accelerated failure time models , Statistics and Probability Letters , 2022 , 181109275
  • Controlling the false discovery rate for latent factors via unit-rank deflation , Statistics and Probability Letters , 2021 , 178109178
  • Innovated scalable efficient inference for ultra-large graphical models , Statistics and Probability Letters , 2021 , 173109085
  • Innovated scalable dynamic learning for time-varying graphical models , Statistics and Probability Letters , 2020 , 165: 1-6
  • 基于 ADMM 算法的网络连接数据变量选择 , 计算机系统应用 , 2022 , 31(1): 1-10