Corpus ID: 202777693

Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond

@inproceedings{Banerjee2019RandomQF,
  title={Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond},
  author={A. Banerjee and Q. Gu and V. Sivakumar and Z. Wu},
  booktitle={NeurIPS},
  year={2019}
}

A. Banerjee, Q. Gu, +1 author Z. Wu

Published in NeurIPS 2019

Computer Science, Mathematics

Several important families of computational and statistical results in machine learning and randomized algorithms rely on uniform bounds on quadratic forms of random vectors or matrices. Such results include the Johnson-Lindenstrauss (J-L) Lemma, the Restricted Isometry Property (RIP), randomized sketching algorithms, and approximate linear algebra. The existing results critically depend on statistical independence, e.g., independent entries for random vectors, independent rows for random… CONTINUE READING

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