STAT992-Shao(Spring 2010)

STAT 992: Variable Selection

Instructor:
Prof. Jun Shao
MSC 1235A
(608)-262-7938
shao@stat.wisc.edu

Schedule for Stat 992

Introduction by Jun Shao

Presentation-1 by Qi Tang
Presentation-2 by Qi Tang

On model selection consistency of Lasso by P. Zhao and B. Yu
Presentation by Jie Zhang

High dimensional graphs and variable selection with the Lasso by N. Meinshausen and P. Buhlmann
Presentation by Jee Young Moon

The sparsity and bias of the Lasso selection in high-dimensional linear regression by C.-H. Zhang and J. Huang
Presentation by Quefeng Li

High-dimensional generalized linear models and the Lasso by S.A. van de Geer
Presentation by Bin Dai

Sure independence screening for ultrahigh dimensional feature space by J. Fan and J. Lv
Presentation by Jingjiang Peng

Variable selection via nonconcave penalized likelihood and its oracle properties by J. Fan and R. Li
Presentation by Yang Zhao

Nonconcave penalized likelihood with diverging number of parameters by J. Fan and H. Peng
Presentation by Jiale Xu

The adaptive Lasso and its oracle properties by H. Zou
Presentation by Dongjun Chung

A unified approach to model selection and sparse recovery using regularized least squares by J. Lv and Y. Fan
Presentation by Quoc Tan Tran

Sure independence screening in generalized linear models with NP-dimensionality by J. Fan and R. Song
Presentation by Jiwei Zhao

Shrinkage tuning parameter selection with a diverging number of parameters by H. Wang, B. Li, and C. Leng
Presentation by Xu He

Asymptotic properties of bridge estimators in sparse high-dimensional regression models by J. Huang, J. Horowitz and S. Ma
Presentation by Minjing Tao

High-dimensional variable selection by L. Wasserman and K. Roeder
Presentation by Xinxin Yu

Mixture of g priors for Bayesian variable selection by F. Liang, R. Paulo, G. Molina, M.A. Clyde, and J.O. Berger
Presentation by Sheng Zhang

Bayesian variable selection by Z. Shang and M. Clayton
Presentation by Zuofeng Shang