Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow

@inproceedings{Zhang2016ProvableNP,
  title={Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow},
  author={Huishuai Zhang and Yuejie Chi and Yingbin Liang},
  booktitle={ICML},
  year={2016}
}
Solving systems of quadratic equations is a central problem in machine learning and signal processing. One important example is phase retrieval, which aims to recover a signal from only magnitudes of its linear measurements. This paper focuses on the situation when the measurements are corrupted by arbitrary outliers, for which the recently developed non-convex gradient descent Wirtinger flow (WF) and truncated Wirtinger flow (TWF) algorithms likely fail. We develop a novel median-TWF algorithm… CONTINUE READING
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Lowrank solutions of linear matrix equations via procrustes flow

  • S. Tu, R. Boczar, M. Soltanolkotabi, B. Recht
  • arXiv preprint arXiv:1507.03566,
  • 2015
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