Joint multi-label classification and label correlations with missing labels and feature selection
作者：
Highlights：
• Joint multi-label classification with label correlations and feature selection.
• Obtaining the high-order asymmetric label correlations automatically by learning.
• Selecting the shared sparse feature structure among labels by l2,1-norm.
• Dealing with both full labels and missing labels cases.
摘要
•Joint multi-label classification with label correlations and feature selection.•Obtaining the high-order asymmetric label correlations automatically by learning.•Selecting the shared sparse feature structure among labels by l2,1-norm.•Dealing with both full labels and missing labels cases.
论文关键词：Multi-label classification,Label correlations,Missing labels,Feature selection,ℓ2,1-norm
论文评审过程：Received 18 March 2018, Revised 9 August 2018, Accepted 14 August 2018, Available online 1 September 2018, Version of Record 21 November 2018.
论文官网地址：https://doi.org/10.1016/j.knosys.2018.08.018
