报告时间：2023年03月16日 14:05开始
报 告 人：李冲（浙江大学 教授）
报告地点：包玉书9号楼113报告厅
报告题目：Linearized proximal algorithms with adaptive stepsizes for convex composite optimization with applications
报告摘要：In this talk, we continue to study the problem of numerically solving convex composite optimizations. Linearized proximal algorithms (LPA) with adaptive stepsizes for solving the convex composite optimization problem are proposed. Local and/or global convergence properties of the proposed algorithms are explored, and their superlinear/quadratic convergence results are established under the assumptions of local weak sharp minima and the quasi-regularity condition. Our proposed algorithms, compared with the LPA with the constant stepsize, have the advantages of suiting for wider range of problems and of employing higher convergence rates. We apply the LPA with adaptive stepsizes to solve the wireless sensor network localization problem, and the numerical results show that the LPA with adaptive stepsizes can solve this problem more efficiently and stable than the LPA with the constant stepsize or other algorithms
报告人简介： 李冲，浙江大学数学系教授，博士生导师。主要从事非线性优化理论与计算、数值泛函分析、数值代数、稀疏优化及其应用、机器学习等领域的研究。先后主持国家自然科学基金及省部级项目等近二十项，出版专著1部，在SCI期刊上发表论文近200篇，特别是在优化理论和计算数学的顶级刊物SIAM J Optim., Math. Program，SIAM J. Control Optim. 以及SIAM J.Numer. Anal 上发表论文 30余篇。1992年起享受国务院政府特殊津贴，原商业部有突出贡献的中青年专家、江苏省第七届青年科学家等，2004年获教育部首届新世纪优秀人才计划资助。
