报告题目：Linearized proximal algorithms with adaptive stepsizes for convex composite optimization with applications
报告人：李冲教授(浙江大学)
报告地点：尚贤楼706报告厅
报告时间：2019年5月24日上午10:00-11:00
主持人：徐玮玮副教授
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,获浙江大学博士学位，主要从事Banach空间理论、非光滑分析、非线性逼近与优化、数值泛函分析等领域的研究, 在SCI期刊上发表论文近200篇， 特别是在计算数学和优化理论的顶级刊物SIAM J Optim., Math. Program，SIAM J.Numer. Anal.以及SIAM J. Control Optim.上发表论文近30篇。曾任台湾数学杂志(SCI) ，现任《高等学校计算数学学报》以及多个国际刊物的编委。先后主持中国国家自然科学基金、西班牙及南非国家自然科学基金等十余项，出版专著1部， 曾获浙江省教委科技进步奖一、二等奖等奖励，享受国务院政府特殊津贴专家、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。
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数学与统计学院
2019年5月23日