A greedy EM algorithm for Gaussian mixture learning

DOI10.1023/A:1013844811137zbMath1008.68734OpenAlexW1570876803MaRDI QIDQ1857734

Nikos Vlassis, Aristidis Likas

Publication date: 19 February 2003

Published in: Neural Processing Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1013844811137

zbMATH Keywords

EM algorithmGaussian mixturegreedy learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies and applications (68U99)

Related Items (13)

Finite skew-mixture models for estimation of positive false discovery rates ⋮ Automatic learning of cost functions for graph edit distance ⋮ Newtonian clustering: an approach based on molecular dynamics and global optimization ⋮ Survey on speech emotion recognition: features, classification schemes, and databases ⋮ Mini-batch learning of exponential family finite mixture models ⋮ An Improved Kernel K-means Clustering Algorithm ⋮ Online Learning of Single- and Multivalued Functions with an Infinite Mixture of Linear Experts ⋮ Adaptive Gaussian Process Approximation for Bayesian Inference with Expensive Likelihood Functions ⋮ Efficient Greedy Learning of Gaussian Mixture Models ⋮ A novel semi-supervised multi-view clustering framework for screening Parkinson's disease ⋮ A BYY scale-incremental EM algorithm for Gaussian mixture learning ⋮ Maximum likelihood inference for mixtures of skew Student-\(t\)-normal distributions through practical EM-type algorithms ⋮ Mixture of Experts Classification Using a Hierarchical Mixture Model

This page was built for publication: A greedy EM algorithm for Gaussian mixture learning