Because for regular maximum likelihood estimation, it's too cunsuming to calculate the normalization factor. But without normalization factor, we can't calculate the conditional probability used in maximum likelihood estimation.

University of Michigan - Ann Arbor

The key idea of noise constractive estimation is to learn the feature of data distribution by learning from a dichotomy problem of selecting the data points from the original dataset from a mixed dataset made up of noises and the original datasets.

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