TY - GEN
T1 - Bayesian multiview dimensionality reduction for learning predictive subspaces
AU - Gönen, Mehmet
AU - Gönen, Gülefşan Bozkurt
AU - Gürgen, Fikret
N1 - Publisher Copyright:
© 2014 The Authors and IOS Press.
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84923195000&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84923195000&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-419-0-387
DO - 10.3233/978-1-61499-419-0-387
M3 - Conference contribution
AN - SCOPUS:84923195000
T3 - Frontiers in Artificial Intelligence and Applications
SP - 387
EP - 392
BT - ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings
A2 - Schaub, Torsten
A2 - Friedrich, Gerhard
A2 - O'Sullivan, Barry
PB - IOS Press BV
T2 - 21st European Conference on Artificial Intelligence, ECAI 2014
Y2 - 18 August 2014 through 22 August 2014
ER -