Corpus ID: 226222395

Wasserstein Distributionally Robust Optimization and Variation Regularization.

@article{Gao2017WassersteinDR,
  title={Wasserstein Distributionally Robust Optimization and Variation Regularization.},
  author={R. Gao and Xi Chen and A. Kleywegt},
  journal={arXiv: Learning},
  year={2017}
}
  • R. Gao, Xi Chen, A. Kleywegt
  • Published 2017
  • Computer Science, Mathematics
  • arXiv: Learning
  • Wasserstein distributionally robust optimization (DRO) has recently achieved empirical success for various applications in operations research and machine learning, owing partly to its regularization effect. Although connection between Wasserstein DRO and regularization has been established in several settings, existing results often require restrictive assumptions, such as smoothness or convexity, that are not satisfied for many problems. In this paper, we develop a general theory on the… CONTINUE READING
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