Gaussian Mixture Models: Expectation-Maximization

In course

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Description

This lecture covers Gaussian Mixture Models, focusing on the Expectation-Maximization algorithm to optimize likelihood estimation. It explains the challenges with K-means, the advantages of GMM, and the EM algorithm steps.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_p5dlr27y

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Statistical hypothesis testing, Bayesian statistics

Information engineering

Machine learning: Unsupervised learning

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