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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
  • Reproducible feature selection for high-dimensional measurement error models , INFORMS Journal on Computing , 2025 , 37(5)1352-1370
  • 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 , 231-45
  • Scalable interpretable multi-response regression via SEED , Journal of Machine Learning Research , 2019 , 201-34
  • The constrained Dantzig selector with enhanced consistency , Journal of Machine Learning Research , 2016 , 171-22
  • Using machine learning to advance disparities research: Subgroup analyses of access to opioid treatment , Health Services Research , 2022 , 57411-421
  • 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 , 311935-1959
  • 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 , 1791-14
  • Uniform joint screening for ultra-high dimensional graphical models , Journal of Multivariate Analysis , 2020 , 1791-13
  • Balanced estimation for high-dimensional measurement error models , Computational Statistics and Data Analysis , 2018 , 12678-91
  • Scalable efficient reproducible multi-task learning via data splitting , Statistics and Probability Letters , 2024 , 208110071
  • 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 , 1651-6