Joint hypergraph learning and sparse regression for feature selection

作者：

Highlights：

• We have proposed a hypergraph learning approach for feature selection.

• The approach simultaneously learns hyperedge weights and does feature selection.

• The learned hyperedge weights better characterize the manifold structure of the data.

摘要

•We have proposed a hypergraph learning approach for feature selection.•The approach simultaneously learns hyperedge weights and does feature selection.•The learned hyperedge weights better characterize the manifold structure of the data.

论文关键词：Feature selection,Hypergraph learning,Sparse regression

论文评审过程：Received 8 August 2015, Revised 18 May 2016, Accepted 14 June 2016, Available online 9 July 2016, Version of Record 21 October 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.06.009