Optimal Orthogonal Group Synchronization and Rotation Group Synchronization
Statistics Theory
2022-04-27 v2 Optimization and Control
Machine Learning
Statistics Theory
Abstract
We study the statistical estimation problem of orthogonal group synchronization and rotation group synchronization. The model is where is a Gaussian random matrix and is either an orthogonal matrix or a rotation matrix, and each is observed independently with probability . We analyze an iterative polar decomposition algorithm for the estimation of and show it has an error of when initialized by spectral methods. A matching minimax lower bound is further established which leads to the optimality of the proposed algorithm as it achieves the exact minimax risk.
Cite
@article{arxiv.2109.13491,
title = {Optimal Orthogonal Group Synchronization and Rotation Group Synchronization},
author = {Chao Gao and Anderson Y. Zhang},
journal= {arXiv preprint arXiv:2109.13491},
year = {2022}
}