汇报标题 (Title)：New gradient methods for smooth unconstrained optimization problems（光滑无约束优化问题的新梯度步骤）
汇报人 (Speaker)： 孙聪 副教授（北京邮电大学）
汇报功夫 (Time)：2023年9月26日 (周二) 10:00
汇报地址 (Place)：校本部F309
约请人(Inviter)：徐姿 教授
主办部门：理学院数学系
汇报提要：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.
