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李高荣教授学术报告

  发布日期:2017-06-12  浏览量:470


报告题目: Graphical Knockoff Filter for High-dimensional Regression Models

: 李高荣(北京工业大学教授,博士生导师)

报告时间: 2017615(周四)  15:30-16:30

报告地点: 磬苑校区澳门赌搏网站大全H306

报告摘要:Controlling the false discovery rate (FDR) is a hot and challenging topic in the multiple hypothesis testing problems, especially for the high-dimensional regression models. In this paper, we propose a new proposal on knockoff filter, called as graphical knockoff filter, to consider the high-dimensional linear regression model with the Gaussian random design. We can obtain the efficient estimator of the precision matrix based on the estimation theory of ultra-large Gaussian graphical models, which can help us to construct the cheap knockoff variable beautifully as a control group in the high-dimensional setting. It is important that the graphical knockoff procedure can directly be used to select the significant variable with nonzero coefficients efficiently while bounding FDR under the help of Lasso solution. The properties of the proposed graphical knockoff procedures are investigated both theoretically and numerically. It is shown that the proposed graphical knockoff procedure asymptotically controls FDR at the target level q and has the higher statistical power. Simulation results show that the proposed graphical knockoff procedure performs well numerically in terms of both the empirical false discovery rate and power of the test. A real data is analyzed to assess the performance of the proposed graphical knockoff procedure.

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                                            2017612

专家概况: 李高荣,北京工业大学教授,博士生导师。主要研究方向是复杂高维数据分析、深度学习、模型和变量选择、非参数统计、经验似然、纵向数据和测量误差模型等。于20077月在北京工业大学应用数理学院获得概率论与数理统计专业博士学位,20078月到20096月在华东师范大学金融与统计学院从事博士后研究工作,20163月到20173月为美国南加州大学Marshall商学院博士后。迄今为止,在T-he Annals of Statistics》、《Statistics and Comp-uting》、《Journal of Multivariate Analysis》、《Stati-stica Sinica和《Computa-tional Statistics and Data Analysis》等国内外重要学术期刊发表学术论文70多篇,其中40多篇发表在国际SCI期刊,在科学出版社出版专著《纵向数据半参数模型》和《现代测量误差模型》。入选北京市属高等学校人才强教深化计划中青年骨干人才培养计划和北京市优秀人才培养资助计划和北京工业大学京华人才”。

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