On the integration of topic modeling and dictionary learning

Lingbo Li, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

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. Copyright 2011 by the author(s)/owner(s).
Original languageEnglish (US)
Title of host publicationProceedings of the 28th International Conference on Machine Learning, ICML 2011
Pages625-632
Number of pages8
StatePublished - Oct 7 2011
Externally publishedYes

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