一、报告题目：ByMI: Byzantine Machine Identification with False Discovery Rate Control

二、报告人：南开大学统计与数据科学学院-邹长亮教授

三、报告时间：2024年4月20日星期六下午14:40

四、报告地点：数统学院会议室80602

五、摘要：Various robust estimation methods or algorithm shave been proposed to hedge against Byzantine failures in distributed learning. However, there is a lack of systematic approaches to provide theoretic alguarantees of significance in detecting those Byzantine machines. We develop a general detection procedure, ByMI, via error rate control to address this issue, which is applicable to many robust learning problems. The key idea is to apply the sample-splitting strategy on each worker machine to construct a score statistic integrated with a general robust estimation and then to utilize the symmetry property of those scores to derive a data-driven threshold. The proposed method is dimension insensitive and p-value free with the elp of the symmetry property can achieve false discovery rate control under mild conditions. Numerical experiments on both synthetic and real data validate the theoretical results and demonstrate the effectiveness of our proposed method.

邹长亮，南开大学统计与数据科学学院教授、统计研究院院长。2008年博士毕业于南开大学，随后留校任教。主要从事统计学及其与数据科学领域的交叉研究和应用。研究兴趣包括：高维数据统计推断、大规模数据流分析、变点和异常点检测等，在统计学和机器学习相关领域的顶尖杂志《Annals of Statistics》《Biometrika》《Journal of the American Statistical Association》《.Journal of Machine Learning Research》上发表论文二十余篇，入选爱思唯尔“中国高被引学者”。主持国家基金委优青、杰青、重点项目、重大项目课题和科技部重点研发计划课题等。任教育部科技委委员、全国应用统计专业硕士教学指导委员会委员、中国现场统计研究会副理事长等。