Multi-Frequency Phase Synchronization

被引:0
作者
Gao, Tingran [1 ]
Zhao, Zhizhen [2 ]
机构
[1] Univ Chicago, Comm Computat & Appl Math, Dept Stat, Chicago, IL 60637 USA
[2] Univ Illinois, Dept Elect & Comp Engn, Coordinated Sci Lab, Chicago, IL 60680 USA
来源
INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 97 | 2019年 / 97卷
关键词
MULTIDIMENSIONAL HARMONIC RETRIEVAL; SEMIDEFINITE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
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页数:10
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