Iterated conditional modes

Iterated Conditional Modes (ICM) is an optimization algorithm typically used in statistical inference and computer vision, particularly within the context of Markov Random Fields (MRFs) and related models. It is a variant of the more general "Conditional Modes" approach and is primarily employed for estimating the maximum a posteriori (MAP) configuration of a set of variables, given a probabilistic model.