• Corpus ID: 218581492

An Investigation of Why Overparameterization Exacerbates Spurious Correlations

@article{Sagawa2020AnIO,
  title={An Investigation of Why Overparameterization Exacerbates Spurious Correlations},
  author={Shiori Sagawa and Aditi Raghunathan and Pang Wei Koh and Percy Liang},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.04345}
}
We study why overparameterization -- increasing model size well beyond the point of zero training error -- can hurt test error on minority groups despite improving average test error when there are spurious correlations in the data. Through simulations and experiments on two image datasets, we identify two key properties of the training data that drive this behavior: the proportions of majority versus minority groups, and the signal-to-noise ratio of the spurious correlations. We then analyze a… 

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