Unsupervised feature selection by regularized self-representation

作者：

Highlights：

• A regularized self-representation (RSR) model is proposed for unsupervised feature selection.

• An iterative reweighted least-squares algorithm is proposed to solve the RSR model.

• The proposed method shows superior performance to state-of-the-art.

摘要

Highlights•A regularized self-representation (RSR) model is proposed for unsupervised feature selection.•An iterative reweighted least-squares algorithm is proposed to solve the RSR model.•The proposed method shows superior performance to state-of-the-art.

论文关键词：Self-representation,Unsupervised feature selection,Sparse representation,Group sparsity

论文评审过程：Received 8 January 2014, Revised 16 July 2014, Accepted 9 August 2014, Available online 19 August 2014.

论文官网地址：https://doi.org/10.1016/j.patcog.2014.08.006