2) Convex optimization problem 凸优化问题 1. This paper discusses problems arising in system and control theory to a few standard convex optimization problems involving linear matrix inequality(LMI). 本文研究了出现在系统与控制理论中的一些标准的、包含线性矩阵不等式的凸优化问题。 更多例句>> 3) ...
Duchi, John C., and Feng Ruan. "Stochastic methods for composite and weakly convex optimization ...
Common methods for identifying global optimal points and values of nonconvex optimization problems are based on branch-and-bound ideas. This chapter presents the 伪 \\alpha BB method as an exemplary branch-and-bound procedure. One way to efficiently calculate the lower bounds required there is ...
近几年ICMl,NIPS 出现了许多Non-Convex Optimization的论文, 我虽然也在看Non-Convex Optimization,但是我仅在读论文的摘要和和老师交流的时候略微感受可能有这几个原因(不局限于): 1> Deep Learning 大部分的目标函数是Non-Convex的。 2> 如今出现了一些处理Non-Convex问题的理论技巧和方法。 但是具体为什么Non-C...
Nonconvex Optimization Problems 来自 Springer 喜欢 0 阅读量: 1 作者: Stein, Oliver 摘要: Common methods for identifying global optimal points and values of nonconvex optimization problems are based on branch-and-bound ideas. This chapter presents the α \alpha BB method as an exemplary branch-...
The LMI (linear matrix inequality)-based Hinfinity controller synthesis theory guarantees that if the controller is allowed to have the same order as the plant, and every system matrix of the controller is freely tunable, then the Hinfinity optimization problem can be solved by convex optimization...
分享者:林义尊博士 主题:Efficient Solvers for Non-smooth Convex Optimization Problems 时间:2022年6月2日(星期四)11:00 – 12:00 地点:暨南大学番禺校区暨伯学院三楼303会议室(食堂对面三层小楼) 报告人简介:林义尊,博士、暨南大学信息科...
Thenonconvexglobal optimization problems are methodic al ly similar to the partial convex optimization problems,which had been studied by the author. 利用非凸优化问题中的Lagrange对偶性思想 ,对可行集进行恰当的细划 ,证明了求解相应的Lagrangian对偶问题所获得的剖分对偶界在适当的假设条件下收敛到原问题的最...
The subject of this paper is a decomposition algorithm of the augmented price-type (Lagrange multiplier method) using the augmented Lagrange function for solving complex structured nonconvex optimization problems. The algorithms of that method known to date were applicable for problems with only equality...
Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and ...