![](/__local/9/E3/98/A5DE79D1FCFDDD09C45AE382060_F13A7544_2B3C.jpg)
李培丽
姓名:李培丽
职称:讲师
办公室:九章学堂南楼C座301
邮箱:lipeili@henu.edu.cn
研究方向:统计优化
教育背景:2010.09-2014.06,学士,BEVITOR伟德APP官网,数学与应用数学
2014.09-2017.06,硕士,BEVITOR伟德APP官网,运筹学与控制论
2017.09-2020.06,博士,武汉大学,计算数学
工作经历:2020.07-2022.06,博士后,华东师范大学,统计学
2022.07-至今,BEVITOR伟德APP官网,讲师
研究领域:运筹学、统计学
代表性学术论文:
1. Yanyun Ding, Haibin Zhang, Peili Li, Yunhai Xiao. An efficient semismooth Newton method for adaptive sparse signal reconstruction problems. Optimization Methods & Software, 2022, in press.
2. Peili Li, Min Liu, Zhou Yu. A global two-stage algorithm for non-convex penalized high-dimensional linear regression problems. Computational Statistics, 2022:1-28.
3. Peili Li, Yuling Jiao, Xiliang Lu, Lican Kang. A data-driven line search rule for support recovery in high-dimensional data analysis. Computational Statistics & Data Analysis, 2022, 174:107524.
4. Peili Li, Xiliang Lu, Yunhai Xiao. Smoothing Newton method for L0-L2 regularized linear inverse problem. Inverse Problems and Imaging, 2022, 16(1):153-177.
5. Yunhai Xiao, Peili Li, Sha Lu. Sparse estimation of high-dimensional inverse covariance matrices with explicit eigenvalue constraints. Journal of the Operations Research Society of China, 2021, 9(3):543-568.
6. Can Wu, Yunhai Xiao, Peili Li. Semi-proximal augmented lagrangian method for sparse estimation of high-dimensional inverse covariance matrices. Journal of Applied and Numerical Optimization, 2020, 2(2):155-169.
7. Peili Li, Yunhai Xiao. An efficient algorithm for sparse inverse covariance matrix estimation based on dual formulation. Computational Statistics & Data Analysis, 2018, 128:292-307.