• Corpus ID: 220281081

Unbiased Loss Functions for Extreme Classification With Missing Labels

@article{Schultheis2020UnbiasedLF,
  title={Unbiased Loss Functions for Extreme Classification With Missing Labels},
  author={Erik Schultheis and Mohammadreza Qaraei and Priyanshu Gupta and Rohit Babbar},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.00237}
}
The goal in extreme multi-label classification (XMC) is to tag an instance with a small subset of relevant labels from an extremely large set of possible labels. In addition to the computational burden arising from large number of training instances, features and labels, problems in XMC are faced with two statistical challenges, (i) large number of 'tail-labels' -- those which occur very infrequently, and (ii) missing labels as it is virtually impossible to manually assign every relevant label… 

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