Expanding the role of mixture models in statistical analyses of big data

该项目旨在开发理论程序，以扩展推理和学习算法，以分析大数据集。它将开发分析工具和算法来分析大数据集，而传统的推理方法由于数据的复杂性或大小而无法直接分析这些大数据集。这将加速科学发现和创新的进展，例如导致新的研究领域；通过对人类和社会进程和相互作用的研究增进了解；促进经济增长和改善健康和生活质量。这样的应用应该在科学、工程、医学、商业、教育和国家安全方面带来突破性的发现和创新。

This project aims to develop theoretical procedures to scale inference and learning algorithms to analyse big data sets. It will develop analytic tools and algorithms to analyse big data sets which classical methods of inference cannot analyse directly due to the data’s complexity or size. This will accelerate the progress of scientific discovery and innovation, leading, for example, to new fields of inquiry; to an increase in understanding from studies on human and social processes and interactions; and to the promotion of economic growth and improved health and quality of life. Such applications should lead to breakthrough discoveries and innovation in science, engineering, medicine, commerce, education and national security.