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.

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 - 2011
Externally published	Yes
Event	28th International Conference on Machine Learning, ICML 2011 - Bellevue, WA, United States Duration: Jun 28 2011 → Jul 2 2011

Publication series

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

Other

Other	28th International Conference on Machine Learning, ICML 2011
Country/Territory	United States
City	Bellevue, WA
Period	6/28/11 → 7/2/11

All Science Journal Classification (ASJC) codes

Computer Science Applications
Human-Computer Interaction
Education

Cite this

@inproceedings{981f8158e64a4f229cb4b8d7f51c11a3,

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.",

author = "Lingbo Li and Mingyuan Zhou and Guillermo Sapiro and Lawrence Carin",

year = "2011",

language = "English (US)",

isbn = "9781450306195",

series = "Proceedings of the 28th International Conference on Machine Learning, ICML 2011",

pages = "625--632",

booktitle = "Proceedings of the 28th International Conference on Machine Learning, ICML 2011",

note = "28th International Conference on Machine Learning, ICML 2011 ; Conference date: 28-06-2011 Through 02-07-2011",

}

Li, L, Zhou, M, Sapiro, G & Carin, L 2011, On the integration of topic modeling and dictionary learning. in Proceedings of the 28th International Conference on Machine Learning, ICML 2011. Proceedings of the 28th International Conference on Machine Learning, ICML 2011, pp. 625-632, 28th International Conference on Machine Learning, ICML 2011, Bellevue, WA, United States, 6/28/11.

On the integration of topic modeling and dictionary learning. / Li, Lingbo; Zhou, Mingyuan; Sapiro, Guillermo et al.
Proceedings of the 28th International Conference on Machine Learning, ICML 2011. 2011. p. 625-632 (Proceedings of the 28th International Conference on Machine Learning, ICML 2011).

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

TY - GEN

T1 - On the integration of topic modeling and dictionary learning

AU - Li, Lingbo

AU - Zhou, Mingyuan

AU - Sapiro, Guillermo

AU - Carin, Lawrence

PY - 2011

Y1 - 2011

N2 - 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.

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.

UR - http://www.scopus.com/inward/record.url?scp=80053450173&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80053450173&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:80053450173

SN - 9781450306195

T3 - Proceedings of the 28th International Conference on Machine Learning, ICML 2011

SP - 625

EP - 632

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

T2 - 28th International Conference on Machine Learning, ICML 2011

Y2 - 28 June 2011 through 2 July 2011

ER -

On the integration of topic modeling and dictionary learning

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Other files and links

Fingerprint

Cite this