Innovations in sparse optimisation: big data nonsmooth optimisation

稀疏优化的创新：大数据非光滑优化

• 批准号: DP190100555
• 负责人: Prof Guoyin Li
• 金额: $ 23.17万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2019
• 资助国家: 澳大利亚
• 起止时间: 2019-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP190100555
• 关键词: Innovations; sparse; optimisation; big; data

This project aims to produce innovative optimisation methods capable of solving a wide range of practical problems that are currently too complex to be solved. Optimisation involving huge data sets is ubiquitous. Sparse optimisation has emerged as a challenging frontier of modern optimisation because it effectively computes an optimal solution with desired low complexity structure so that a resulting solution can be efficiently stored, implemented and utilised, and is robust to the data inexactness. This project aims at developing innovative mathematical techniques and efficient numerical schemes for solving sparse optimisation problems. The intended outcomes will have significant impact on many areas of science, medicine and engineering, where sparse optimisation is used, including cancer radiotherapy optimal planning.

该项目旨在产生创新的优化方法，能够解决目前过于复杂而无法解决的各种实际问题。涉及庞大数据集的优化无处不在。稀疏优化已经成为现代优化的一个具有挑战性的前沿，因为它有效地计算出具有所需低复杂度结构的最优解，从而可以有效地存储，实现和利用所得到的解决方案，并且对数据不精确性具有鲁棒性。该项目旨在开发创新的数学技术和有效的数值方案来解决稀疏优化问题。预期结果将对使用稀疏优化的许多科学、医学和工程领域产生重大影响，包括癌症放射治疗优化规划。