Contrastive Estimation

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This is a method proposed by Smith and Eisner 2005:Contrastive Estimation: Training Log-Linear Models on Unlabeled Data.

The proposed approach deals with the estimation of log-linear models (e.g. Conditional Random Fields) in an unsupervised fashion. The method focuses on the denominator of the log-linear models by exploiting the so called implicit negative evidence.

Motivation

Problem Formulation

The Algorithm

Some Reflections

Related Papers