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荔园学者Colloquium第一百八十八期

讲座题目：A General Stabilization Framework to FDR Control with Applications

主讲人：钟威 教授（厦门大学)

讲座时间：2026年11月22日15：30-16:30

讲座地点：深圳大学粤海校区汇研楼601会议室

内容摘要：Stability is a basic requirement for reproducible data analysis: conclusions should not be overly sensitive to small changes in the data or the way they are analyzed. This talk focuses on stable discovery under false discovery rate (FDR) control. FDR control limits the expected proportion of false discoveries, but selected sets can still vary across repeated analyses of the same data due to randomness of the algorithms. We present the FDR Stabilizer, a general framework for improving stability in multiple testing and variable selection. The method combines evidence from repeated analyses into a single ranking and determines the selection size from the rounded average number of discoveries. Finite-sample bounds compare its FDR and power with those of the original procedure, while asymptotic results establish conditions for FDR control without power loss. We also study how the selected set stabilizes as the number of repetitions increases. Two extensions illustrate further developments of this framework. In skeleton learning for high-dimensional directed acyclic graphs, false edges can mislead network interpretation and subsequent causal analysis, while unknown conditioning sets and dependent tests complicate FDR control. In multiple change-point detection, false alarms can suggest structural changes that never occurred. Candidate locations also vary across analyses, requiring stabilization of both the number and locations of detected changes. We develop extensions for both problems, with more stable selections and asymptotic FDR guarantees.

主讲人简介：钟威，厦门大学王亚南经济研究院、经济学院统计学与数据科学系，南强特聘教授（二级教授）、博士生导师。国家重大人才工程领军人才（教育部，2024），国家自科优秀青年基金获得者（2019）。同时兼任厦门大学国际合作与交流处处长、台港澳事务办公室主任、海外办学事务办公室主任。主要从事高维数据统计分析、统计学习算法、计量经济学等研究。先后担任JASA、ISR等6个国内外期刊的编委（AE），在AOS、JASA、Biometrika、JoE、JBES、JMLR、AOAS、《中国科学-数学》、《统计研究》等国内外统计学权威期刊发表（含接收）50多篇论文。曾获霍英东教育基金会高等院校青年科学奖、第九届高等学校科学研究优秀成果奖、全国宝钢优秀教师奖，以及厦门大学青年教师技能比赛特等奖, 厦门大学 “我最喜爱的十位老师”， 厦门大学南强卓越教学团队负责人等，主编教育部统计学101计划教材《人工智能的统计基础》。

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　　　　　　　　　　　　　　　　　　2026年11月9日