Multi-dimensional clustering through fusion of high-order similarities

作者：

Highlights：

• An adaptively high-order similarity measurement is designed.

• The high-order similarity exploits potential relationship within each space.

• The ordinary and high-order similarity regularization is collaboratively optimized.

摘要

•An adaptively high-order similarity measurement is designed.•The high-order similarity exploits potential relationship within each space.•The ordinary and high-order similarity regularization is collaboratively optimized.

论文关键词：High-order similarity,Low-rank,Multi-dimensional clustering,Spectral clustering

论文评审过程：Received 16 May 2019, Revised 29 August 2020, Accepted 9 June 2021, Available online 6 July 2021, Version of Record 22 August 2021.

论文官网地址：https://doi.org/10.1016/j.patcog.2021.108108