Multi-view collaborative locally adaptive clustering with Minkowski metric

作者：

Highlights：

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

• Our approach exploits the complementary information from different views.

• Our approach is robust to the outliers in multi-view dataset.

• This paper introduces the L-p metric for different multi-view clustering tasks.

• Extensive experiments have been conducted to show the effectiveness.

摘要

•This paper proposes a new multi-view subspace clustering approach.•Our approach exploits the complementary information from different views.•Our approach is robust to the outliers in multi-view dataset.•This paper introduces the L-p metric for different multi-view clustering tasks.•Extensive experiments have been conducted to show the effectiveness.

论文关键词：Clustering,Multi-view clustering,Subspace clustering,Locally adaptive clustering,Collaborative strategy,Minkowski metric

论文评审过程：Received 25 December 2016, Revised 28 April 2017, Accepted 29 May 2017, Available online 2 June 2017, Version of Record 8 June 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.05.076