报告人：彭柳华 (澳大利亚墨尔本大学)
报告题目：Distributed Statistical Inference for Massive Data
报告摘要：This project considers distributed statistical inference for general symmetric statistics in the context of massive data where the data can be stored at multiple platforms in di?erent lo-cations. In order to facilitate e?ective computation and to avoid expensive communication among di?erent platforms, we formulate distributed statistics which can be conducted over smaller data blocks. The statistical properties of the distributed statistics are investigated in terms of the mean square error of estimation and asymptotic distributions with respect to the number of data blocks. In addition, we propose two distributed bootstrap algorithms which are computationally e?ective and are able to capture the underlying distribution of the distributed statistics. Numeri-cal simulation and real data applications of the proposed approaches are provided to demonstrate the empirical performance.
报告人简介：彭柳华，现任职于澳大利亚墨尔本大学数学与统计学院。2006-2013年就读于南开大学数学学院，获得学士和硕士学位。2017在美国爱荷华州立大学获得统计博士学位。毕业后作为讲师就职于墨尔本大学。主要研究方向是bootstrap，大数据的分块式算法理论，高维数据分析等。
报告时间：2018年11月30日（星期五）下午3：00 - 4：00.
报告地点：科技楼南楼702
