题 目：A parallel splitting augmented Lagrangian method for two-block separable convex programming with application in image processing

主讲人：刘静博士

时 间：2023年2月28日（周二）13：30-14：30

地 点：6号学院楼500会议室

主办单位：伟德BETVlCTOR1946源于英国 浙江省2011“数据科学与大数据分析协同创新中心”

摘要：

The augmented Lagrangian method (ALM) is one of the most successful first order methods for convex programming with linear equality constraints. To solve the two-block separable convex minimization problem,we always use the parallel splitting ALM method. In this paper, we will show that no matter how small the step size and the penalty parameter are, the convergence of the parallel splitting ALM is not guaranteed. We propose a new convergent parallel splitting ALM (PSALM), which is the regularizing ALM’s minimization subproblem by some simple proximal terms. In application this new PSALM is used to solve video background extraction problems and our numerical results indicate that this new PSALM is efficient.

主讲人简介：

刘静，同济大学管理学博士，研究方向是最优化理论与方法及其在图像处理、管理科学中的应用。在国内外权威学术刊物上发表论文20余篇。

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