Symmetric Norm Estimation and Regression on Sliding Windows

@article{Braverman2021SymmetricNE,
  title={Symmetric Norm Estimation and Regression on Sliding Windows},
  author={Vladimir Braverman and Viska Wei and Samson Zhou},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.01635}
}
The sliding window model generalizes the standard streaming model and often performs better in applications where recent data is more important or more accurate than data that arrived prior to a certain time. We study the problem of approximating symmetric norms (a norm on R that is invariant under sign-flips and coordinate-wise permutations) in the sliding window model, where only the W most recent updates define the underlying frequency vector. Whereas standard norm estimation algorithms for… 

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