Bayesian multiview dimensionality reduction for learning predictive subspaces

Mehmet Gonen, Gülefşan Bozkurt Gönen, Fikret Gürgen

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

3 Citations (Scopus)

Abstract

Multiview learning basically tries to exploit different feature representations to obtain better learners. For example, in video and image recognition problems, there are many possible feature representations such as color- and texture-based features. There are two common ways of exploiting multiple views: forcing similarity (i) in predictions and (ii) in latent subspace. In this paper, we introduce a novel Bayesian multiview dimensionality reduction method coupled with supervised learning to find predictive subspaces and its inference details. Experiments show that our proposed method obtains very good results on image recognition tasks in terms of classification and retrieval performances.

Original languageEnglish (US)
Title of host publicationECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings
PublisherIOS Press
Pages387-392
Number of pages6
Volume263
ISBN (Print)9781614994183
DOIs
StatePublished - 2014
Event21st European Conference on Artificial Intelligence, ECAI 2014 - Prague, Czech Republic
Duration: Aug 18 2014Aug 22 2014

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume263
ISSN (Print)09226389

Other

Other21st European Conference on Artificial Intelligence, ECAI 2014
CountryCzech Republic
CityPrague
Period8/18/148/22/14

Fingerprint

Image recognition
Supervised learning
Textures
Color
Experiments

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Gonen, M., Gönen, G. B., & Gürgen, F. (2014). Bayesian multiview dimensionality reduction for learning predictive subspaces. In ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings (Vol. 263, pp. 387-392). (Frontiers in Artificial Intelligence and Applications; Vol. 263). IOS Press. https://doi.org/10.3233/978-1-61499-419-0-387

Bayesian multiview dimensionality reduction for learning predictive subspaces. / Gonen, Mehmet; Gönen, Gülefşan Bozkurt; Gürgen, Fikret.

ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings. Vol. 263 IOS Press, 2014. p. 387-392 (Frontiers in Artificial Intelligence and Applications; Vol. 263).

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

Gonen, M, Gönen, GB & Gürgen, F 2014, Bayesian multiview dimensionality reduction for learning predictive subspaces. in ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings. vol. 263, Frontiers in Artificial Intelligence and Applications, vol. 263, IOS Press, pp. 387-392, 21st European Conference on Artificial Intelligence, ECAI 2014, Prague, Czech Republic, 8/18/14. https://doi.org/10.3233/978-1-61499-419-0-387
Gonen M, Gönen GB, Gürgen F. Bayesian multiview dimensionality reduction for learning predictive subspaces. In ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings. Vol. 263. IOS Press. 2014. p. 387-392. (Frontiers in Artificial Intelligence and Applications). https://doi.org/10.3233/978-1-61499-419-0-387
Gonen, Mehmet ; Gönen, Gülefşan Bozkurt ; Gürgen, Fikret. / Bayesian multiview dimensionality reduction for learning predictive subspaces. ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings. Vol. 263 IOS Press, 2014. pp. 387-392 (Frontiers in Artificial Intelligence and Applications).
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