Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net

A new approach to regression regularization called the Pairwise Elastic Net is proposed. Like the Elastic Net, it simultaneously performs automatic variable selection and continuous shrinkage. In addition, the Pairwise Elastic Net encourages the grouping of strongly correlated predictors based on a pairwise similarity measure. We give examples of how the approach can be used to achieve the objectives of Ridge regression, the Lasso, the Elastic Net, and Group Lasso. Finally, we present a coordinate descent algorithm to solve the Pairwise Elastic Net.

• Type: Journal
• Year: 2010
• Where: JMLR
• Authors: Alexander Lorbert, David Eis, Victoria Kostina, David M. Blei, Peter J. Ramadge
• Keywords: Elastic Net, JMLR 2010, Pairwise Elastic Net, Pairwise Similarity Measure