石跃勇

Gender : Male

School/Department : 经济管理学院


Personal Profile

2013年毕业于武汉大学数学与统计学院概率论与数理统计专业。现就职于中国地质大学(武汉)经济管理学院统计学系。目前研究领域主要为统计计算。主持国家自然科学基金青年项目1项 (2019.01-2021.12), 发表论文20余篇。


  1. Cao Y, Kang L, Li X, Liu Y, Luo Y, Shi Y. Newton-Raphson meets sparsity: sparse learning via a novel penalty and a fast solver[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023, https://doi.org/10.1109/TNNLS.2023.3251748.

  2. Huang J, Jiao Y, Lu X, Shi Y, Yang Q, Yang Y. PSNA: A pathwise semismooth Newton algorithm for sparse recovery with optimal local convergence and oracle properties[J]. Signal Processing, 2022, 194(108432).

  3. Kang Y, Shi Y, Jiao Y, Li W, Xiang D. Fitting jump additive models[J]. Computational Statistics and Data Analysis, 2021, 162: 107266.

  4. Hu A, Jiao Y, Liu Y, Shi Y, Wu Y. Distributed quantile regression for massive heterogeneous data[J]. Neurocomputing, 2021, 448: 249–262.

  5. Shi Y, Huang J, Jiao Y, Kang Y, Zhang H. Generalized Newton-Raphson algorithm for high dimensional LASSO regression[J]. Statistics and Its Interface, 2021, 14(3): 339–350.

  6. 焦雨领, 刘妍岩, 石跃勇, 徐志斌. 带辅助协变量的相关失效时间数据的加权估计伪部分似然方法[J]. 中国科学 : 数学, 2021, 51(7): 1191–1212.

  7. Shi Y, Huang J, Jiao Y, Yang Q. A semi-smooth Newton algorithm for high-dimensional nonconvex sparse learning[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(8): 2993–3006.

  8. Cao Y, Shi Y, Yu J. Statistical inference for the accelerated failure time model under two-stage generalized case-cohort design[J]. Communications in Statistics-Theory and Methods, 2019, 48(24): 6063–6079.

  9. Shi Y, Zhou Z, Jiao Y, Wang J. A primal dual active set with continuation algorithm for high-dimensional nonconvex SICA-penalized regression[J]. Journal of Statistical Computation and Simulation, 2019, 89(5): 864–883.

  10. Shi Y, Xu D, Cao Y, Jiao Y. Variable selection via generalized SELO-penalized Cox regression models[J]. Journal of Systems Science and Complexity, 2019, 32(2): 709–736.

  11. 张虎, 曹永秀, 焦雨领, 石跃勇. ℓ⁰ 正则化下衰减信号稀疏恢复的 PDASC 算法[J]. 中国科学: 信息科学, 2019, 49(7): 900–910.

  12. Shi Y, Jiao Y, Cao Y, Liu Y. An alternating direction method of multipliers for MCP-penalized regression with high-dimensional data[J]. Acta Mathematica Sinica, English Series, 2018, 34(12): 1892–1906.

  13. Shi Y, Cao Y, Jiao Y, Yu J. A note on power calculation for generalized case-cohort sampling with accelerated failure time model[J]. Journal of Mathematics, 2018, 38(2): 200–208.

  14. Shi Y, Cao Y, Yu J, Jiao Y. High-dimensional variable selection with the generalized SELO penalty[J]. Journal of Mathematics, 2018, 38(6): 900–998.

  15. Shi Y, Wu Y, Xu D, Jiao Y. An ADMM with continuation algorithm for non-convex SICA-penalized regression in high dimensions[J]. Journal of Statistical Computation and Simulation, 2018, 88(9): 1826–1846.

  16. Shi Y, Cao Y, Yu J, Jiao Y. Variable selection via generalized SELO-penalized linear regression models[J]. Applied Mathematics-A Journal of Chinese Universities, 2018, 33(2): 145–162.

  17. 曹永秀, 焦雨领, 石跃勇, 刘妍岩. Cox比例风险模型中基于SELO惩罚函数的变量选择方法[J]. 中国科学: 数学, 2018, 48(5): 643–660.

  18. Shi Y, Jiao Y, Yan L, Cao Y. A modified BIC tuning parameter selector for SICA-penalized Cox regression models with diverging dimensionality[J]. Journal of Mathematics, 2017, 37(4): 723–730.

  19. Yu J, Shi Y, Yang Q, Liu Y. Additive hazards regression under generalized case-cohort sampling[J]. Acta Mathematica Sinica, English Series, 2014, 30(2): 251–260.

  20. Shi Y, Cao Y, Jiao Y, Liu Y. SICA for Cox’s proportional hazards model with a diverging number of parameters[J]. Acta Mathematicae Applicatae Sinica, English Series, 2014, 30(4): 887–902.