Corpus ID: 211082829

List-Decodable Subspace Recovery via Sum-of-Squares

@article{Bakshi2020ListDecodableSR,
  title={List-Decodable Subspace Recovery via Sum-of-Squares},
  author={Ainesh Bakshi and Pravesh Kothari},
  journal={ArXiv},
  year={2020},
  volume={abs/2002.05139}
}
  • Ainesh Bakshi, Pravesh Kothari
  • Published in ArXiv 2020
  • Computer Science, Mathematics
  • We give the first efficient algorithm for the problem of list-decodable subspace recovery. Our algorithm takes input $n$ samples $\alpha n$ ($\alpha\ll 1/2$) are generated i.i.d. from Gaussian distribution $\mathcal{N}(0,\Sigma_*)$ on $\mathbb{R}^d$ with covariance $\Sigma_*$ of rank $r$ and the rest are arbitrary, potentially adversarial outliers. It outputs a list of $O(1/\alpha)$ projection matrices guaranteed to contain a projection matrix $\Pi$ such that $\|\Pi-\Pi_*\|_F^2 = \kappa^4 \log… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 43 REFERENCES

    List-decodable linear regression, CoRR abs/1905.05679 (2019)

    • Sushrut Karmalkar, Adam R. Klivans, Pravesh K. Kothari
    • 2019

    An Overview of Robust Subspace Recovery

    Efficient algorithms for outlierrobust regression, Conference On Learning Theory, COLT 2018

    • Adam R. Klivans, Pravesh K. Kothari, Raghu Meka
    • Stockholm, Sweden,
    • 2018