• Corpus ID: 88524272

Permutation Weighting

@inproceedings{Arbour2021PermutationW,
  title={Permutation Weighting},
  author={David T. Arbour and Drew Dimmery},
  booktitle={ICML},
  year={2021}
}
This work introduces permutation weighting: a weighting estimator for observational causal inference under general treatment regimes which preserves arbitrary measures of covariate balance. We show that estimating weights which obey balance constraints is equivalent to a simple binary classification problem between the observed data and a permuted dataset (no matter the cardinality of treatment). Arbitrary probabilistic classifiers may be used in this method; the hypothesis space of the… 
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