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，WilliamHill中文官方网站，数学与应用数学

2014.09-2017.06，硕士，WilliamHill中文官方网站，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，WilliamHill中文官方网站，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.