Global likelihood maximization is an important aspect of many statistical analyses. Often the likelihood function is highly multi-extremal. This presents a significant challenge t...
This paper introduces a novel solver, namely cross entropy (CE), into the MRF theory for medical image segmentation. The solver, which is based on the theory of rare event simulati...
— Metaheuristics such as Estimation of Distribution Algorithms and the Cross-Entropy method use probabilistic modelling and inference to generate candidate solutions in optimizat...
Marcus Gallagher, Ian Wood, Jonathan M. Keith, Geo...
Nonlinear random effects models with finite mixture structures are used to identify polymorphism in pharmacokinetic/ pharmacodynamic (PK/PD) phenotypes. An EM algorithm for maxim...
Xiaoning Wang, Alan Schumitzky, David Z. D'Argenio
We present the CEM (Conditional Expectation Maximization) algorithm as an extension of the EM (Expectation Maximization) algorithm to conditional density estimation under missing ...