COLLABORATIVE TARGETED MAXIMUM LIKELIHOOD LEARNING

A method is provided comprising: determining one or more initial distribution estimators of a true probability distribution; determining for each series of estimators of a nuisance parameter; generating candidate targeted estimators of the probability distribution for a targeted feature using an iterative modification of the initial distribution estimator(s) designed to reduce bias in the estimate of the target feature with respect to the initial distribution estimator, based on the series of estimators and the targeted feature; selecting one of the candidate estimators as an estimator for the true probability distribution for the targeted feature; and applying a mapping to the estimator for the true probability distribution or relevant portion thereof to obtain an estimated value for the targeted feature.