ML Anthology

On the Integration of Topic Modeling and Dictionary Learning

Lingbo Li, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin
ICML 2011 pp. 625-632
/icml/2011/li2011icml-integration/

Abstract

A new nonparametric Bayesian model is developed to integrate dictionary learning and topic model into a unified framework. The model is employed to analyze partially annotated images, with the dictionary learning performed directly on image patches. Efficient inference is performed with a Gibbs-slice sampler, and encouraging results are reported on widely used datasets.

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Text

Li et al. "On the Integration of Topic Modeling and Dictionary Learning." International Conference on Machine Learning, 2011.

Markdown

[Li et al. "On the Integration of Topic Modeling and Dictionary Learning." International Conference on Machine Learning, 2011.](https://mlanthology.org/icml/2011/li2011icml-integration/)

BibTeX

@inproceedings{li2011icml-integration,
  title     = {{On the Integration of Topic Modeling and Dictionary Learning}},
  author    = {Li, Lingbo and Zhou, Mingyuan and Sapiro, Guillermo and Carin, Lawrence},
  booktitle = {International Conference on Machine Learning},
  year      = {2011},
  pages     = {625-632},
  url       = {https://mlanthology.org/icml/2011/li2011icml-integration/}
}