Optimal orthogonal group synchronization and rotation group synchronization

IF 1.4 4区 数学 Q2 MATHEMATICS, APPLIED Information and Inference-A Journal of the Ima Pub Date : 2022-08-01 DOI:10.1093/imaiai/iaac022
Chao Gao;Anderson Y Zhang
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引用次数: 7

Abstract

We study the statistical estimation problem of orthogonal group synchronization and rotation group synchronization. The model is $Y_{ij} = Z_i^* Z_j^{*T} + \sigma W_{ij}\in{\mathbb{R}}^{d\times d}$ where $W_{ij}$ is a Gaussian random matrix and $Z_i^*$ is either an orthogonal matrix or a rotation matrix, and each $Y_{ij}$ is observed independently with probability $p$ . We analyze an iterative polar decomposition algorithm for the estimation of $Z^*$ and show it has an error of $(1+o(1))\frac{\sigma ^2 d(d-1)}{2np}$ when initialized by spectral methods. A matching minimax lower bound is further established that leads to the optimality of the proposed algorithm as it achieves the exact minimax risk.
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最优正交群同步和旋转群同步
研究了正交群同步和旋转群同步的统计估计问题。该模型为$Y_{ij}=Z_i^*Z_j^{*T}+\mathbb{R}}^{d \ times d}$中的σW_{ij}$,其中$W_{ij}$是高斯随机矩阵,$Z_i^**$是正交矩阵或旋转矩阵,并且每个$Y_。我们分析了一种用于$Z^*$估计的迭代极分解算法,并表明当用谱方法初始化时,它的误差为$(1+o(1))\frac{\sigma^2 d(d-1)}{2np}$。进一步建立了匹配的极小极大下界,该下界导致所提出的算法的最优性,因为它实现了精确的极小极大风险。
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来源期刊
CiteScore
3.90
自引率
0.00%
发文量
28
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