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Gilbert Saporta教授讲座通知

发布日期:2018-09-20      点击量:

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【北航经管学术论坛】

GilbertSaporta教授讲座通知

题目:ASURVEYOFSOME “SPARSE” METHODSFORHIGHDIMENSIONALDATA

主讲人:Prof.GilbertSaporta

时间:2018年9月25日(周二),14:30-16:00pm

地点:新主楼B221

邀请人:王惠文 教授

摘要:

High dimensional data means that the number of variablespis far larger than the number of observationsn. This occurs in several fields such as genomic data or chemometrics.

Whenp>nthe OLS estimator does not exist for linear regression. Since it is a case of forced multicollinearity, one may use regularized techniques such as ridge regression, principal component regression or PLS regression: these methods provide rather robust estimates through a dimension reduction approach or with explicit (or not) constraints on the regression coefficients. The fact that all the predictors are kept is often considered as a positive point.

However, ifp>>nit becomes a drawback since a combination of all variables cannot be interpreted. Sparse combinations,i.e.with a large number of zero coefficients are preferred. The Lasso consists in finding the estimate, which performs simultaneously regularization and variable selection thanks to a L1penalty. We will present variants such as sparse PLS and the group-lasso when the variables are structured in blocks.

主讲人简介:

GilbertSaporta教授,法国巴黎第六大学博士学位,现任法国统计学会荣誉主席,法国国立工艺学院(CNAM)荣誉教授。曾担任国际统计学会副主席和国际统计计算学会主席。GilbertSaporta教授长期从事数据分析相关基础科学研究,指导了27名博士,发表专著2部,高水平学术论文80余篇。

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