Nature

Expectation-Maximization Algorithms in Statistical Inference

The expectation-maximization (EM) algorithm is a cornerstone technique for parameter estimation in statistical models that incorporate latent variables or incomplete data. By iteratively alternating ...
Nature

An expectation–maximization algorithm for the Lasso estimation of quantitative trait locus effects

The least absolute shrinkage and selection operator (Lasso) estimation of regression coefficients can be expressed as Bayesian posterior mode estimation of the regression coefficients under various ...
IEEE

Convergence of the Expectation-Maximization Algorithm Through Discrete-Time Lyapunov Stability Theory

Abstract: In this paper, we propose a dynamical systems perspective of the Expectation-Maximization (EM) algorithm. More precisely, we can analyze the EM algorithm as a nonlinear state-space dynamical ...
IEEE

Convergence of Expectation-Maximization Algorithm With Mixed-Integer Optimization

Abstract: The convergence of expectation-maximization (EM)-based algorithms typically requires continuity of the likelihood function with respect to all the unknown parameters (optimization variables) ...