Corpus ID: 229923068

The Sample Complexity of Robust Covariance Testing

@article{Diakonikolas2020TheSC,
  title={The Sample Complexity of Robust Covariance Testing},
  author={Ilias Diakonikolas and D. Kane},
  journal={ArXiv},
  year={2020},
  volume={abs/2012.15802}
}

Ilias Diakonikolas, D. Kane

Published 2020

Computer Science, Mathematics

ArXiv

We study the problem of testing the covariance matrix of a high-dimensional Gaussian in a robust setting, where the input distribution has been corrupted in Huber’s contamination model. Specifically, we are given i.i.d. samples from a distribution of the form Z = (1− ǫ)X + ǫB, where X is a zero-mean and unknown covariance Gaussian N (0,Σ), B is a fixed but unknown noise distribution, and ǫ > 0 is an arbitrarily small constant representing the proportion of contamination. We want to distinguish… CONTINUE READING

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