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Robustly Learning any Clusterable Mixture of Gaussians

Cited by: 12|Views72
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Abstract

We study the efficient learnability of high-dimensional Gaussian mixtures in the outlier-robust setting, where a small constant fraction of the data is adversarially corrupted. We resolve the polynomial learnability of this problem when the components are pairwise separated in total variation distance. Specifically, we provide an algori...More

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