On the integration of topic modeling and dictionary learning

Lingbo Li; Mingyuan Zhou; Guillermo Sapiro; Lawrence Carin

On the integration of topic modeling and dictionary learning

Lingbo Li, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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 language	English (US)
Title of host publication	Proceedings of the 28th International Conference on Machine Learning, ICML 2011
Pages	625-632
Number of pages	8
State	Published - Oct 7 2011
Externally published	Yes

Cite this

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title = "On the integration of topic modeling and dictionary learning",

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).",

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AB - 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).

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M3 - Conference contribution

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BT - Proceedings of the 28th International Conference on Machine Learning, ICML 2011

ER -

On the integration of topic modeling and dictionary learning

Abstract

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