报告题目 (Title)：New gradient methods for smooth unconstrained optimization problems（光滑无约束优化问题的新梯度方法）

报告人 (Speaker)： 孙聪 副教授（北京邮电大学）

报告时间 (Time)：2023年9月26日 (周二) 10:00

报告地点 (Place)：校本部F309

邀请人(Inviter)：徐姿 教授

主办部门：理学院数学系

报告摘要：In this talk, a new gradient method for unconstrained optimization problem is proposed, where the stepsizes are updated in a cyclic way, and the Cauchy step is approximated by the quadratic interpolation. Combined with the adaptive non-monotone line search technique, we prove the global convergence of this method. Moreover, the algorithms have sublinear convergence rate for general convex functions and R-linear convergence rate for strongly convex problems. The numerical results show that our proposed algorithm outperforms the benchmark methods.