Effective Algorithms for Structured Nonconvex Optimization Based on First- and Second-Order Methods and Convex Relaxations

基于一阶、二阶方法和凸松弛的结构化非凸优化的有效算法

• 批准号: 2445089
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2445089
• 关键词: Effective; Algorithms; Structured; Nonconvex; Optimization

This project is concerned with the development and implementation of effective algorithms for nonconvex optimization problems with a particular underlying structure (e.g., quadratic programs on compact sets, optimization problems arising from machine learning applications). The project is aimed at utilising first-order and second-order information together with various convex relaxations and convex envelopes in an attempt to obtain increasingly tighter upper and lower bounds on the optimal value. The proposed methods will be implemented and tested on benchmark instances.

该项目关注的是具有特定底层结构的非凸优化问题的有效算法的开发和实现（例如，紧集上的二次规划，由机器学习应用引起的优化问题）。该项目旨在利用一阶和二阶信息以及各种凸松弛和凸包络，以获得越来越严格的最佳值的上限和下限。所提出的方法将在基准实例上实现和测试。