• Corpus ID: 245650182

Optimal Representations for Covariate Shift

@article{Ruan2022OptimalRF,
  title={Optimal Representations for Covariate Shift},
  author={Yangjun Ruan and Yann Dubois and Chris J. Maddison},
  journal={ArXiv},
  year={2022},
  volume={abs/2201.00057}
}
Machine learning systems often experience a distribution shift between training and testing. In this paper, we introduce a simple variational objective whose optima are exactly the set of all representations on which risk minimizers are guaranteed to be robust to any distribution shift that preserves the Bayes predictor, e.g., covariate shifts. Our objective has two components. First, a representation must remain discriminative for the task, i.e., some predictor must be able to simultaneously… 

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