Researchers detail exact recovery for community detection in dependent Gaussian mixture models

This paper investigates the problem of exact recovery for community detection within Gaussian mixture models. The research focuses on scenarios with dependent and heterogeneous Gaussian noise, where the noise covariance matrix can be non-diagonal and even singular. The authors derive sufficient conditions for exact recovery of the maximum likelihood estimator, influenced by a "\Sigma-whitened separation" metric and local comparison inequalities. AI

排序理由 This is a research paper published on arXiv detailing a novel statistical method. [lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv stat.ML 阅读 →

• arXiv
• MLE
• Moore--Penrose inverse
• Zhongyang Li
• Gaussian Mixture Models

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