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

  title={Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow},
  author={Huishuai Zhang and Yuejie Chi and Yingbin Liang},
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
Highly Cited
This paper has 56 citations. REVIEW CITATIONS
37 Citations
36 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 37 extracted citations

57 Citations

Citations per Year
Semantic Scholar estimates that this publication has 57 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 36 references

Lowrank solutions of linear matrix equations via procrustes flow

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

Similar Papers

Loading similar papers…