arXiv Machine Learning
Aug 19

Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixtures

arXiv:2506. 06584v2 Announce Type: replace Abstract: Learning Gaussian Mixture Models (GMMs) is a fundamental problem in statistics and machine learning, with the Expectation-Maximization (EM) algorithm and its popular variant gradient EM being arguably the most widely used algorithms in practice.

By Mo Zhou, Weihang Xu, Maryam Fazel, Simon S. Du