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"Learning Stable Classifiers by Transferring Unstable Features" ICML 2022

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Tofu

Code and data for Learning Stable Classifiers by Transferring Unstable Features ICML 2022

If you like this work and use it on your own research, please cite our paper.

@inproceedings{bao2022learning,
  title={Learning Stable Classifiers by Transferring Unstable Features},
  author={Bao, Yujia and Chang, Shiyu and Barzilay, Regina},
  booktitle={International Conference on Machine Learning},
  pages={1483--1507},
  year={2022},
  organization={PMLR}
}

Get started

Setup conda

  1. Create a new conda environment with the required dependencies conda env create --file environment.yml
  2. Activate the environment conda activate tofu

Download the datasets

  • You can download the datasets by running the script bin/download_data.sh. All datasets will be downloaded under datasets/

Run some experiments

  • bin/beer.sh transfer from aspect look to aspect aroma
  • bin/ask2me.sh transfer from task penetrance to task incidence
  • bin/bird.sh transfer from seabird to waterbird
  • bin/mnist.sh transfer from even to odd
  • bin/celeba.sh transfer from eyeglasses to blond hair

Acknowledgements

Research was sponsored by the United States Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under Cooperative Agreement Number FA8750-19-2-1000. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.

🌈 This paper is dedicated to the memory of our beloved family member Tofu, who filled our lives with so many wuffs and wuvs.

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