Convergence of Gradient EM on Multi-component Mixture of Gaussians

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017), pp. 6959-6969, 2017.

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Abstract:

In this paper, we study convergence properties of the gradient variant of Expectation-Maximization algorithm [11] for Gaussian Mixture Models for arbitrary number of clusters and mixing coefficients. We derive the convergence rate depending on the mixing coefficients, minimum and maximum pairwise distances between the true centers, dimens...More

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