讲师
太阳成集团tyc151cc-太阳成集团tyc7111cc >> 师资队伍 >> 全职教工 正文李培丽
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，河南大学，数学与应用数学
2014.09-2017.06，硕士，河南大学，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，河南大学，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.