Convergence of the Expectation Maximization algorithm revisited

Quand : 8 septembre 2026 à 11:15

Où : 1R3, 1er étage

Organisé par : Institut Henri Poincaré

The EM-algorithm assures monotone increase of the incomplete data likelihood, but does not in general guarantee convergence of the parameter estimates. We take a fresh look at the situation and present novel sufficient conditions for convergence that are conveniently verifiable in practical situations. Illustrations with typical applications of the EM-algorithm are given. Key words: Kullback-Leibl