papers: supervised or discriminative topic model

Topic models are originally designed for topic discovery/clustering, not for classification. To use topic models for classification task, we have modify the structure of the topic model to add the class label and use it to bias the topic discovery process.

the following paper present some supervised/discriminative topic models by machine learning guys:

• MedLDA: Maximum Margin Supervised Topic Models for Regression and Classification, ICML 2009
• DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification, NIIPS 2008
• Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora, EMNLP 2009
• Supervised topic models, NIPS 2007

some supervised/discriminative topic models by computer vision guys:

• A Bayesian Hierarchical Model for Learning Natural Scene Categories, CVPR 2005
  
• Simultaneous Image Classification and Annotation, CVPR 2009
• Spatially coherent latent topic model for concurrent object segmentation and classification, ICCV 2007
• Towards Total Scene Understanding Classification, Annotation and Segmentation in an Automatic Framework, CVPR 2009
• What, where and who? Classifying events by scene and object recognition, ICCV 2007
• Learning Hierarchical Models of Scenes, Objects, and Parts, ICCV 2005