题目：The Adaptive Projection Estimator with Enhanced Inference Efficiency

主讲人：中国科学技术大学 郑泽敏教授

主持人：西南财经大学统计学院 常晋源教授

时间：2020年4月28日（星期二）14:30-15:50

直播平台及会议ID：腾讯会议，411 461 022

报告摘要：

As a popular class of methods, inference via the de-biased estimators typically requires a large sample size to guarantee the asymptotic normality and allows a relatively small number of nonzero coefficients above the identifiable level. To alleviate such constraints and enhance the inference efficiency, we develop a new inference procedure via an adaptive projection estimator, which is based on the adaptive orthogonalization vector. This orthogonalization vector is adaptive in that it is orthogonal to the other covariate vectors corresponding to the identifiable coefficients, and at the same time being a relaxed orthogonalization against the remaining unidentifiable covariates. In this way, it completely removes the impacts of identifiable coefficients and controls that of the unidentifiable ones at a neglectable level, yielding much weaker constraint on both the sample size and the number of nonzero coefficients.

主讲人简介：

郑泽敏，中国科学技术大学管理学院教授、统计与金融系主任、博士生导师，主要研究方向是高维统计推断和大数据问题。郑泽敏教授在横跨这一领域的若干关键研究课题上取得了富有创造性的研究成果。他的研究成果发表在Journal of the Royal Statistical Society: Series B（JRSSB）、Annals of Statistics（AOS）、Operations Research（OR）、Journal of Machine Learning Research（JMLR）等国际统计学、机器学习及管理优化顶级期刊上。他的研究取得了南加州大学授予的杰出科研奖和美国数理统计协会颁发的科研新人奖。