Multi-view label embedding

作者：

Highlights：

• This paper presents a novel multi-view label embedding algorithm via latent space learning.

• The diversity and complementarity are well balanced by HSIC in multi-view learning.

• Experiments show that MVLE outperforms the state-of-the-art label embedding methods.

摘要

•This paper presents a novel multi-view label embedding algorithm via latent space learning.•The diversity and complementarity are well balanced by HSIC in multi-view learning.•Experiments show that MVLE outperforms the state-of-the-art label embedding methods.

论文关键词：Multi-label classification,Multi-view label embedding,Label space dimension reduction

论文评审过程：Available online 10 July 2018, Version of Record 17 July 2018.

论文官网地址：https://doi.org/10.1016/j.patcog.2018.07.009