数学学科Seminar第2445讲 基于值函数的双层超参数选择差分凸算法

创建时间:  2023/09/08  龚惠英   浏览次数:   返回

报告题目 (Title):基于值函数的双层超参数选择差分凸算法

报告人 (Speaker):张进 副教授 (南方科技大学)

报告时间:2023年09月08日(周五)15:30

参会方式:线上,腾讯会议514-871-643

邀请人:周安娃

主办部门:理学院数学系

报告摘要:

Bilevel Optimization gains significant attention recently due to its various applications. Gradient-based methods guarantee theoretical convergence to stationary solutions when the lower level of the bilevel program is strongly convex (LLSC) and smooth (LLS) for fixed upper-level variable values. In this talk, we present a sequentially convergent Value Function based Difference-of-Convex Algorithm with inexactness (VF-iDCA). We show that this algorithm achieves stationary solutions without LLSC and LLS assumptions for bilevel programs from a broad class of hyperparameter tuning applications. Extensive numerical experiments justify our theoretical results and show that the proposed VF-iDCA yields superior performance.

上一条:数学学科Seminar第2446讲 无限维域中的随机发展方程

下一条:数学学科Seminar第2444讲 两相不可压缩流的数值分析与模拟


数学学科Seminar第2445讲 基于值函数的双层超参数选择差分凸算法

创建时间:  2023/09/08  龚惠英   浏览次数:   返回

报告题目 (Title):基于值函数的双层超参数选择差分凸算法

报告人 (Speaker):张进 副教授 (南方科技大学)

报告时间:2023年09月08日(周五)15:30

参会方式:线上,腾讯会议514-871-643

邀请人:周安娃

主办部门:理学院数学系

报告摘要:

Bilevel Optimization gains significant attention recently due to its various applications. Gradient-based methods guarantee theoretical convergence to stationary solutions when the lower level of the bilevel program is strongly convex (LLSC) and smooth (LLS) for fixed upper-level variable values. In this talk, we present a sequentially convergent Value Function based Difference-of-Convex Algorithm with inexactness (VF-iDCA). We show that this algorithm achieves stationary solutions without LLSC and LLS assumptions for bilevel programs from a broad class of hyperparameter tuning applications. Extensive numerical experiments justify our theoretical results and show that the proposed VF-iDCA yields superior performance.

上一条:数学学科Seminar第2446讲 无限维域中的随机发展方程

下一条:数学学科Seminar第2444讲 两相不可压缩流的数值分析与模拟