Transfer subspace learning via low-rank and discriminative reconstruction matrix

作者：

Highlights：

• A new approach in unsupervised domain transfer learning is proposed.

• The low rank and sparse constraints are imposed on the reconstruction matrix.

• The discriminative ability of the target and source samples is captured.

• The information content of the reconstruction coefficient matrix is utilized.

摘要

•A new approach in unsupervised domain transfer learning is proposed.•The low rank and sparse constraints are imposed on the reconstruction matrix.•The discriminative ability of the target and source samples is captured.•The information content of the reconstruction coefficient matrix is utilized.

论文关键词：Transductive transfer learning,Reconstruction matrix,Subspace learning,Discriminative capability of target domains

论文评审过程：Received 5 February 2018, Revised 16 August 2018, Accepted 19 August 2018, Available online 22 August 2018, Version of Record 21 November 2018.

论文官网地址：https://doi.org/10.1016/j.knosys.2018.08.026