Multi-Frequency Phase Synchronization

Abstract

We propose a novel formulation for phase synchronization—the statistical problem of jointly estimating alignment angles from noisy pairwise comparisons—as a nonconvex optimization problem that enforces consistency among the pairwise comparisons in multiple frequency channels. Inspired by harmonic retrieval in signal processing, we develop a simple yet efficient two-stage algorithm that leverages the multi-frequency information. We demonstrate in theory and practice that the proposed algorithm significantly outperforms state-of-the-art phase synchronization algorithms, at a mild computational costs incurred by using the extra frequency channels. We also extend our algorithmic framework to general synchronization problems over compact Lie groups.

Cite

Text

Gao and Zhao. "Multi-Frequency Phase Synchronization." International Conference on Machine Learning, 2019.

Markdown

[Gao and Zhao. "Multi-Frequency Phase Synchronization." International Conference on Machine Learning, 2019.](https://mlanthology.org/icml/2019/gao2019icml-multifrequency/)

BibTeX

@inproceedings{gao2019icml-multifrequency,
  title     = {{Multi-Frequency Phase Synchronization}},
  author    = {Gao, Tingran and Zhao, Zhizhen},
  booktitle = {International Conference on Machine Learning},
  year      = {2019},
  pages     = {2132-2141},
  volume    = {97},
  url       = {https://mlanthology.org/icml/2019/gao2019icml-multifrequency/}
}