Exploiting Geometries of Learning for Fast, Adaptive and Robust AI

利用学习几何实现快速、自适应和鲁棒的人工智能

• 批准号: DP230101176
• 负责人: Prof Dinh Phung
• 金额: $ 29.59万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP230101176
• 关键词: Exploiting; Geometries; Learning; Fast; Adaptive

This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capability and competitiveness in AI, and deliver robust and trustworthy learning technology. The project should provide significant benefits not only in advancing scientific and translational knowledge but also in accelerating AI innovations, safeguarding cyberspace, and reducing the burden on defence expenses in Australia.

该项目旨在独特地利用深度学习中的几何流形，以推进网络安全和一般认知任务中人工智能(AI)研究和应用的前沿。它希望为机器学习系统开发新的理论、算法、工具和技术，这些系统即使在有限的监督下也是快速、自适应、终身和健壮的。预期结果将增强澳大利亚在人工智能领域的能力和竞争力，并提供稳健和值得信赖的学习技术。该项目不仅应在促进科学和翻译知识方面提供重大好处，而且还应在加速人工智能创新、保护网络空间和减轻澳大利亚国防开支负担方面提供重大好处。