Approximate sparse recovery: optimizing time and measurements

@inproceedings{Gilbert2010ApproximateSR,
  title={Approximate sparse recovery: optimizing time and measurements},
  author={Anna C. Gilbert and Yi Li and Ely Porat and Martin Strauss},
  booktitle={STOC},
  year={2010}
}
A Euclidean <i>approximate sparse recovery</i> system consists of parameters k,N, an m-by-N <i>measurement matrix</i>, Φ, and a decoding algorithm, D. Given a vector, x, the system approximates x by ^x=D(Φ x), which must satisfy ||<sup>x</sup> - x||<sub>2</sub>≤ C ||x - x<sub>k</sub>||<sub>2</sub>, where x<sub>k</sub> denotes the optimal k-term… CONTINUE READING

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