Expectation–Maximization Algorithm

An iterative method for finding maximum-likelihood parameter estimates in statistical models with latent (hidden) variables by alternating between an expectation step that computes expected sufficient statistics given current parameters and a maximization step that updates parameters to maximize expected likelihood, repeated until convergence.