Expectation Maximization Clustering - Jin, Xin; Han, Jiawei (Encyclopedia of Machine Learning and Data Mining, 2017)
The expectation maximization (EM) based clustering is a probabilistic method to partition data into clusters represented by model parameters. Extensions to the basic EM algorithm include but not limited to the stochastic EM algorithm (SEM), the simulated annealing EM algorithm (SAEM), and the Monte Carlo EM algorithm (MCEM).