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Understanding Private Evolution as Learning-Augmented Clustering

McMillan, Audra et al.
arXiv (All) · Papers
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cryptography-and-security
Private Evolution (PE) is a differentially private algorithm for synthetic data generation. While it can be viewed as a Wasserstein learning algorithm, it performs much better in practice than worst-case Wasserstein analyses would predict. We recast PE as generative model-augmented Wasserstein learn
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