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学术沙龙:Cross-Validation for Optimal and Reproducible Statistical Learning
文:教师发展中心 来源:数学学院 党委教师工作部、人力资源部(教师发展中心) 时间:2018-06-05 4370

  本期“学术沙龙”活动邀请美国明尼苏达大学数学系Yuhong Yang教授来校交流。具体安排如下,欢迎感兴趣的师生参加。

  一、主 题:Cross-Validation for Optimal and Reproducible Statistical Learning

  二、主讲人:明尼苏达大学 Yuhong Yang 教授

  三、时 间:2018年6月8日(周五)10:00-11:00

  四、地 点:清水河校区主楼A1-513

  五、内容简介:

  In data mining and statistical learning, we frequently encounter the task of comparing different methods/algorithms to reach a final choice for pure prediction or a scientific understanding/interpretation of a regression relationship. Cross-validation provides a powerful tool to address the matter. Unfortunately, there are seemingly widespread misconceptions on its use, which can lead to unreliable conclusions. In this talk, we will address the subtle issues involved and present results of minimax optimal regression learning and consistent selection of the best method for the data. In addition, we will propose proper cross-validation tools for model selection diagnostics that will cry foul at an impressive-looking but not really reproducible outcome from a sparse-pattern-hunting method in the wild west of learning with a huge number of covariates.

  六、主讲人简介:

  Yuhong Yang received his Ph.D from Yale in statistics in 1996. He then joined the Department of Statistics at Iowa State University and moved to the University of Minnesota in 2004. His research interests include model selection, multi-armed bandit problems, forecasting, high-dimensional data analysis, and machine learning. He has published in journals in several fields, including Annals of Statistics, IEEE Transaction on Information Theory, Journal of Econometrics, Journal of Approximation Theory, Journal of Machine Learning Research, and International Journal of Forecasting.

  七、主办单位:人力资源部教师发展中心

    承办单位:数学科学学院



                   人力资源部教师发展中心

                     2018年6月5日



编辑:罗莎  / 审核:李果  / 发布:陈伟

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