报告问题 (Title)：Cyclic gradient methods for unconstrained optimization（无约束优化问题的循环梯度法）

报告人 (Speaker)： 孙聪 副教授（北京邮电大学）

报告时间 (Time)：2022年12月13日(周二) 10:00-11:00

报告所在 (Place)：腾讯聚会 (聚会号：225-921-874)

约请人(Inviter)：徐姿

主理部分：理学院数学系

报告摘要：In this work, the cyclic gradient method with Cauchy steps and constructed constant steps for convex quadratic function minimization problems are extended to general smooth unconstrained optimization problems. The Cauchy steps are approximated first by the step-ahead BB steps, and then by the interpolation. The convergence properties of the proposed methods are analyzed. Numerical results show the good performances of the proposed gradient methods compared to the benchmarks.