Contrastive Estimation

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 $\sum _{x\prime ,y\prime }p(x\prime ,y\prime )$ of the log-linear models by exploiting the so called implicit negative evidence in the probability mass.

Motivation

In the Smith and Eisner (2005) paper, the authors have surveyed different estimation techniques for probabilistic graphic model.