Joint representation learning for multi-view subspace clustering

作者：

Highlights：

• This paper proposes a new multi-view subspace clustering method.

• Our method is based on a joint representation learning framework.

• Our method can preserve the view-specific information within each view.

• Our method can capture the complementary information across multiple views.

• Extensive experiments confirm the effectiveness of our method.

摘要

•This paper proposes a new multi-view subspace clustering method.•Our method is based on a joint representation learning framework.•Our method can preserve the view-specific information within each view.•Our method can capture the complementary information across multiple views.•Extensive experiments confirm the effectiveness of our method.

论文关键词：Multi-view subspace clustering,View-specific representation learning,Low-rank tensor representation learning,Unified framework

论文评审过程：Received 12 April 2020, Revised 13 August 2020, Accepted 21 August 2020, Available online 12 September 2020, Version of Record 3 October 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113913