New Aspects on the Modified Group LASSO using the Least Angle Regression and Shrinkage Algorithm

2021 ◽  
Vol 10 (3) ◽  
pp. 527-536
Keyword(s):  
Group Lasso ◽  
Least Angle Regression

scholarly journals A group bridge approach for variable selection

Biometrika ◽  
2009 ◽  
Vol 96 (2) ◽  
pp. 339-355 ◽  
Author(s):  
Jian Huang ◽  
Shuange Ma ◽  
Huiliang Xie ◽  
Cun-Hui Zhang
Keyword(s):  
Variable Selection ◽  
Group Selection ◽  
Group Lasso ◽  
Superior Performance ◽  
Regression Methods ◽  
Least Angle Regression ◽  
Individual Variable ◽  
Bridge Approach ◽  
Selection Property ◽  
Regression Problems

Abstract In multiple regression problems when covariates can be naturally grouped, it is important to carry out feature selection at the group and within-group individual variable levels simultaneously. The existing methods, including the lasso and group lasso, are designed for either variable selection or group selection, but not for both. We propose a group bridge approach that is capable of simultaneous selection at both the group and within-group individual variable levels. The proposed approach is a penalized regularization method that uses a specially designed group bridge penalty. It has the oracle group selection property, in that it can correctly select important groups with probability converging to one. In contrast, the group lasso and group least angle regression methods in general do not possess such an oracle property in group selection. Simulation studies indicate that the group bridge has superior performance in group and individual variable selection relative to several existing methods.

Least Angle Regression Adaptive Incremental Broad Learning System

2020 ◽  
Author(s):  
Fei Chu ◽  
Jiaming Su ◽  
Tao Liang ◽  
Junlong Chen ◽  
Xuesong Wang ◽  
...  
Keyword(s):  
Learning System ◽  
Least Angle Regression

scholarly journals The log-linear group-lasso estimator and its asymptotic properties

Bernoulli ◽  
2012 ◽  
Vol 18 (3) ◽  
pp. 945-974 ◽  
Author(s):  
Yuval Nardi ◽  
Alessandro Rinaldo
Keyword(s):  
Linear Group ◽  
Asymptotic Properties ◽  
Group Lasso ◽  
Log Linear ◽  
Lasso Estimator

Inverse Sparse Group Lasso Model for Robust Object Tracking

2017 ◽  
Vol 19 (8) ◽  
pp. 1798-1810 ◽  
Author(s):  
Yun Zhou ◽  
Jianghong Han ◽  
Xiaohui Yuan ◽  
Zhenchun Wei ◽  
Richang Hong
Keyword(s):  
Object Tracking ◽  
Group Lasso ◽  
Sparse Group Lasso
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