Statistical convergence of the EM algorithm on Gaussian mixture models

DOI10.1214/19-EJS1660zbMath1435.62256arXiv1810.04090MaRDI QIDQ2293721

Yuanzhi Li, Yuekai Sun, Ruofei Zhao

Publication date: 5 February 2020

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1810.04090

zbMATH Keywords

EM algorithmGaussian mixture modelsK-means

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Point estimation (62F10) Numerical mathematical programming methods (65K05)

Related Items (9)

Optimal transport for conditional domain matching and label shift ⋮ Statistical analysis of Markov switching vector autoregression models with endogenous explanatory variables ⋮ Likelihood-based analysis in mixture global vars ⋮ Gaussian graphical model‐based heterogeneity analysis via penalized fusion ⋮ Envelope method with ignorable missing data ⋮ Improved convergence guarantees for learning Gaussian mixture models by EM and gradient EM ⋮ Semiparametric mixture regression with unspecified error distributions ⋮ Maximum likelihood estimation for non-minimum-phase noise transfer function with Gaussian mixture noise distribution ⋮ Grouped spatial autoregressive model

Uses Software

• CHIME

Cites Work

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• The Spectral Method for General Mixture Models
• High-Dimensional Probability
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• An Analysis of the EM Algorithm and Entropy-Like Proximal Point Methods

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