{"title":"最优正交群同步和旋转群同步","authors":"Chao Gao;Anderson Y Zhang","doi":"10.1093/imaiai/iaac022","DOIUrl":null,"url":null,"abstract":"We study the statistical estimation problem of orthogonal group synchronization and rotation group synchronization. The model is \n<tex>$Y_{ij} = Z_i^* Z_j^{*T} + \\sigma W_{ij}\\in{\\mathbb{R}}^{d\\times d}$</tex>\n where \n<tex>$W_{ij}$</tex>\n is a Gaussian random matrix and \n<tex>$Z_i^*$</tex>\n is either an orthogonal matrix or a rotation matrix, and each \n<tex>$Y_{ij}$</tex>\n is observed independently with probability \n<tex>$p$</tex>\n. We analyze an iterative polar decomposition algorithm for the estimation of \n<tex>$Z^*$</tex>\n and show it has an error of \n<tex>$(1+o(1))\\frac{\\sigma ^2 d(d-1)}{2np}$</tex>\n 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.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Optimal orthogonal group synchronization and rotation group synchronization\",\"authors\":\"Chao Gao;Anderson Y Zhang\",\"doi\":\"10.1093/imaiai/iaac022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We study the statistical estimation problem of orthogonal group synchronization and rotation group synchronization. The model is \\n<tex>$Y_{ij} = Z_i^* Z_j^{*T} + \\\\sigma W_{ij}\\\\in{\\\\mathbb{R}}^{d\\\\times d}$</tex>\\n where \\n<tex>$W_{ij}$</tex>\\n is a Gaussian random matrix and \\n<tex>$Z_i^*$</tex>\\n is either an orthogonal matrix or a rotation matrix, and each \\n<tex>$Y_{ij}$</tex>\\n is observed independently with probability \\n<tex>$p$</tex>\\n. We analyze an iterative polar decomposition algorithm for the estimation of \\n<tex>$Z^*$</tex>\\n and show it has an error of \\n<tex>$(1+o(1))\\\\frac{\\\\sigma ^2 d(d-1)}{2np}$</tex>\\n 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.\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2022-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10058607/\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"100","ListUrlMain":"https://ieeexplore.ieee.org/document/10058607/","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 7
摘要
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。
Optimal orthogonal group synchronization and rotation group synchronization
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.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.