题 目: Regularization in Statistics

报告人：黎波博士 清华大学

时 间：2006年11月2日（星期四）下昼2：00－3：00

地 点：伟易博202

Abstract:

We shall give a selective review of the regularization methods

scattered in statistics literature. We introduce a general

conceptual approach to regularization and fit most existing

methods into it. We have tried to focus on the importance of

regularization when dealing with today's high-dimensional objects:

data and models. A wide range of examples are discussed,

including nonparametric regression, boosting, covariance matrix

estimation, principal component estimation, subsampling. This is

a joint work with Prof. Peter J. Bickel.