Multi-Label Learning with Global and Local Label Correlation

@article{Zhu2018MultiLabelLW,
  title={Multi-Label Learning with Global and Local Label Correlation},
  author={Yue Zhu and James T. Kwok and Zhi-Hua Zhou},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2018},
  volume={30},
  pages={1081-1094}
}
It is well-known that exploiting label correlations is important to multi-label learning. Existing approaches either assume that the label correlations are global and shared by all instances; or that the label correlations are local and shared only by a data subset. In fact, in the real-world applications, both cases may occur that some label correlations are globally applicable and some are shared only in a local group of instances. Moreover, it is also a usual case that only partial labels… CONTINUE READING
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