Fast-Lipschitz optimization has been recently proposed as a new framework with numerous computational advantages for both centralized and decentralized convex and non-convex optimization problems. Such a framework generalizes the interference function optimization, which plays an essential role distributed ...
Duchi, John C., and Feng Ruan. "Stochastic methods for composite and weakly convex optimization ...
which have become essential tools in hologram synthesis over the past decades. Concluded from existing optimization algorithms appropriately adapted to CGH inverse problem solving, as is shown in Fig.2b, some crucial factors need to be considered, including constraints, framework, and initialization. Co...
The maximum hands-off control is the optimal solution to the L0 optimal control problem. It has the minimum support length among all feasible control inputs. To avoid computational difficulties arising from its combinatorial nature, the convex approximation method that replaces the L0 norm by the...
测地凸优化 (Geodesic Convex Optimization)就是这么来的 对于优化问题的一般形式：infx∈Kf(x)(1)其...
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 ...
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...
In this paper, we propose a generic algorithmic framework for stochastic proximal quasi-Newton (SPQN) methods to solve non-convex composite optimization problems. Stochastic second-order information is explored to construct proximal subproblem. Under mild conditions we show the non-asympotic convergence...
signal processing and computational statistics is the minimization of non-convex objective functions that may be non-differentiable at the relative boundary of the feasible set. This paper proposes a new family of first- and second-order interior-point methods for non-convex optimization problems with...
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。