Gibbs Max-margin Topic Models with Data Augmentation

10 Oct 2013Jun ZhuNing ChenHugh PerkinsBo Zhang

Max-margin learning is a powerful approach to building classifiers and structured output predictors. Recent work on max-margin supervised topic models has successfully integrated it with Bayesian topic models to discover discriminative latent semantic structures and make accurate predictions for unseen testing data... (read more)

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