On the integration of topic modeling and dictionary learning
Published
Journal Article
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. Copyright 2011 by the author(s)/owner(s).
Duke Authors
Cited Authors
- Li, L; Zhou, M; Sapiro, G; Carin, L
Published Date
- October 7, 2011
Published In
- Proceedings of the 28th International Conference on Machine Learning, Icml 2011
Start / End Page
- 625 - 632
Citation Source
- Scopus