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青年教师学术论坛(1)

发布日期:2021-03-09点击数:

题目:An Introduction to Feature Screening in High Dimension and Model Averaging Prediction

报告人 :夏小超(重庆大学)

日期:2021311

时间:13:30-14:30

地点:数统学院LD202


报告摘要:This talk consists of two parts. In the first part, I will give an introduction to ultrahigh-dimensional feature screening. Specifically, three concrete approaches including: (a) the conditional quantile correlation-based sure independence screening (CQC-SIS) under varying coefficient models, (b) the copula partial correlation-based sure independence screening (CPC-SIS), and (c) a robust partial correlation-based sure independence (RPC-SIS) will be reviewed from our recent work. For each approach, I will present the motivation, methodology, and main theoretical results. Some empirical results would be shown if time permits. In the second part, I will briefly talk about some recent developments of frequentist model averaging prediction, mainly taking the Mallows&apos’s $C_p$ criteria-based model averaging (MMA) as an example.


联系人:夏小超


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重庆大学数学与统计学院的前身是始建于1929年的重庆大学理学院和1937年建立的重庆大学商学院,理学院是重庆大学最早设立的三个学院之一,首任院长为数学家何鲁先生。