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Differentiable Learning Under Triage

This is a repository containing code and data for the paper:

N. Okati, A. De, and M. Gomez-Rodriguez. Differentiable Learning Under Triage. Advances in Neural Information Processing Systems (NeurIPS), 2021.

The paper is available here.

Pre-requisites

This code depends on the following packages:

  1. jupyterlab
  2. Torch
  3. fasttext
  4. matplotlib
  5. numpy

Structure

  • Hatespeech contains the data and code for regenerating the experiments on Hatespeech dataset.
  • Galaxy-zoo contains the data and code for regenerating the experiments on Galaxy-zoo dataset.
  • Synthetic contains the code for regenerating the experiments on Synthetic dataset.

Please refer to section 5 and 6 of our paper for detailed discussion on experiments.

Execution

The details for executing are mentioned inside each folder. Each folder contains a train.ipynb in which our algorithm and baselines are implemented and the results are illustrated.

Citation

Please cite us if you use our work in your research:

@inproceedings{okati2021differentiable,
      title={Differentiable Learning Under Triage}, 
      author={Nastaran Okati and Abir De and Manuel Gomez-Rodriguez},
      booktitle={Advances in Neural Information Processing Systems},
      year={2021}
}