Making Meta-learning Generalised

该项目旨在开发新的机器学习技术，称为广义元学习，使机器更好地利用过去的经验来解决数据较少的新任务。它有望减少当前机器学习对标记数据的不良依赖，并显著扩大其应用范围。该项目的预期成果包括关于元学习的新理论成果和一套创新算法，这些算法可以支持建立下一代计算机视觉系统，以便在开放和动态的环境中工作。通过应用这些先进的智能系统，这应该能够为澳大利亚的科学、社会和经济带来实实在在的好处。

This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the building of next generation of computer vision systems to work in open and dynamic environments. This should be able to produce solid benefits to the science, society, and economy of Australian via the application of these advanced intelligent systems.