Global convergence of gradient descent for phase retrieval

Théodore Fougereux, Cédric Josz, Xiaopeng Li
10/13/2024
math.OCcs.LG

No confident code implementation found for this paper. 3 possible matches can be shown below.

Abstract

We propose a tensor-based criterion for benign landscape in phase retrieval and establish boundedness of gradient trajectories. This implies that gradient descent will converge to a global minimum for almost every initial point.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{fougereux2024global,
  title  = {Global convergence of gradient descent for phase retrieval},
  author = {Théodore Fougereux and Cédric Josz and Xiaopeng Li},
  year   = {2024},
  eprint = {2410.09990},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2410.09990v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2410.09990.svg)](https://codeofpaper.com/paper/2410.09990)

Discussion