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湖南师范大学数学与统计学院导师教师师资介绍简介-卢芳

本站小编 Free考研考试/2021-08-21


卢芳,女,博士,讲师
教育背景:
2007.09-2011.07 周口师范学院 数学与应用数学系 学士
2011.09-2016.07 重庆大学数学与统计学院 运筹学与控制论专业 硕博连读
工作经历:
2017.01-至今 湖南师范大学数学与统计学院 数学系 讲师
教学育人:
本科课程:运筹学、高等数学
科学研究:
研究领域:最优性理论与方法、KKT条件、随机优化
科研项目:
国家自然科学基金青年项目,**,随机向量变分不等式问题的解及其收敛性分析,19万,2019.01-2021.12,主持
湖南省自然科学基金青年项目,2019JJ50378,随机向量变分不等式问题的解及其收敛性分析,5万,2019.01-2021.12,主持
代表性论文(*为通讯作者):
Yang Jing, Tian Guoliang, Lu Fang* and Lu Xuewen (2020). Single-index modal regression via outer product gradients. Computational Statistics & Data Analysis, 144: 106867.
Yang Jing, Lu Fang* and Lu Xuewen (2020). Robust check loss-based inference of semiparametric models and its application in environmental data. Journal of Computational and Applied Mathematics, 365, 112267
Yang Jing*, Lu Fang and Yang Hu (2019). Local Walsh-average based estimation and variable selection for the single-index models. Science China Mathematics, 62, 1977-1996.
Yang Jing*, Lu Fang, Tian Guoliang, Lu Xuewen and Yang Hu (2019). Robust variable selection of varying coefficient partially nonlinear model based on quantile regression. Statistics and Its Interface, 12, 397-413.
Yang Jing*, Lu Fang and Yang Hu (2018). Statistical inference on asymptotic properties of two estimators for the partially linear single-index models. Statistics, 52: 1193-121.
Yang Jing*, Lu Fang and Yang Hu (2018). Quantile regression for robust inference on varying coefficient partially nonlinear models. Journal of the Korean Statistical Society, 47: 172-184.
Yang Jing*, Lu Fang and Yang Hu (2017). Quantile regression for robust estimation and variable selection in partially linear varying-coefficient models. Statistics, 51: 1179-1199.
Lu Fang, Shengjie Li* and Shengkun Zhu (2016). Exact penalization and strong Karush-Kuhn-Tucker conditions for nonsmooth multiobjective optimization problems. Pacific Journal of Optimization, 12(2): 245-261.
Lu Fang and Shengjie Li* (2016). Convexificators and Strong Karush-Kuhn-Tucker Conditions for Nonsmooth Multiobjective Optimization Problems. Pacific Journal of Optimization, 12(4): 699-715.
Lu Fang, Shengjie Li* and Jing Yang (2015). Convergence Analysis of Weighted Expected Residual Method for Nonlinear Stochastic Variational Inequality Problems. Mathematical Methods of Operations Research, 82(2): 229-242.
Lu Fang and Shengjie Li* (2015). Method of Weighted Expected Residual for Solving Stochastic Variational Inequality Problems. Applied Mathematics and Computation, 269: 651-663.
Lu Fang and Chunrong Chen* (2014). Newton-Like Methods for Solving Vector Optimization Problems. Applicable Analysis, 93(8): 1567-1586
联系方式:lf@hunnu.edu.cn

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