报告题目：A quadratically convergent semismooth Newton method for nonlinear semidefinite programming without subdifferential regularity

报告人： 郦旭东 研究员

报告时间：2024年05月13日15：00-17：00

报告地点：数统4号楼312

邀请单位：bat365在线登录入口，福建省应用数学中心（bat365）

报告内容简介：

The non-singularity of generalized Jacobians of the Karush-Kuhn-Tucker (KKT) system is crucial for local convergence analysis of semismooth Newton methods. In this talk, we present a new approach that challenges this conventional requirement. Our discussion revolves around a methodology that leverages some newly developed variational properties, effectively bypassing the necessity for non-singularity of all elements in the generalized Jacobian. Quadratic convergence results of our Newton methods are established without relying on commonly assumed subdifferential regularity conditions. This discussion may offer fresh insights into semismooth Newton methods, potentially paving the way for designing robust and efficient second-order algorithms for general nonsmooth composite optimizations.

报告人简介：

郦旭东，复旦大学大数据学院青年研究员，主要关注数据科学中大规模优化问题的理论、算法及应用，现为Mathematical Programming Computation AE。