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

扩大混合模型在大数据统计分析中的作用

• 批准号: DP170100907
• 负责人: Prof Geoffrey McLachlan
• 金额: $ 23.44万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2017
• 资助国家: 澳大利亚
• 起止时间: 2017-09-30 至 2020-09-29
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP170100907
• 关键词: Expanding; role; mixture; models; statistical

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.

该项目旨在开发理论程序来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，由于数据的复杂性或规模，传统的推理方法无法直接分析这些数据集。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加了解;促进经济增长和改善健康和生活质量。这些应用应导致科学、工程、医学、商业、教育和国家安全方面的突破性发现和创新。