geehokim / Combinatorial-Inference

(NeurIPS 2019) Combinatorial Inference against Label Noise

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Combinatorial Inference against Label Noise

PyTorch implementation of Combinatorial inference framework in the presence of label noise.

Combinatorial Inference against Label Noise

Paul Hongsuck Seo, Geeho Kim, Bohyung Han

Dependencies

This repository is implemented based on PyTorch with Anaconda.

Training models

python train_combinatorial_classifier.py

Citation

If you use this code in a publication, please cite our paper.

@inproceedings{seo2019combinatorial,
  title={Combinatorial inference against label noise},
  author={Seo, Paul Hongsuck and Kim, Geeho and Han, Bohyung},
  booktitle={NeurIPS},
  year={2019}
}

Acknowledgements

This work is partly supported by Google AI Focused Research Award and Korean ICT R&D programs of the MSIP/IITP grant.

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(NeurIPS 2019) Combinatorial Inference against Label Noise


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Language:Python 76.7%Language:Jupyter Notebook 23.3%