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CLC number: TP301

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Received: 2008-03-25

Revision Accepted: 2008-06-01

Crosschecked: 2008-12-26

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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.4 P.504-511


Regularized canonical correlation analysis with unlabeled data

Author(s):  Xi-chuan ZHOU, Hai-bin SHEN

Affiliation(s):  Institute of VLSI Design, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   zhouxc@vlsi.zju.edu.cn, shenhb@yahoo.cn

Key Words:  Canonical correlation analysis (CCA), Regularization, Unlabeled data, Generalized canonical correlation analysis (GCCA)

Xi-chuan ZHOU, Hai-bin SHEN. Regularized canonical correlation analysis with unlabeled data[J]. Journal of Zhejiang University Science A, 2009, 10(4): 504-511.

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author="Xi-chuan ZHOU, Hai-bin SHEN",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

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%T Regularized canonical correlation analysis with unlabeled data
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%A Hai-bin SHEN
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T1 - Regularized canonical correlation analysis with unlabeled data
A1 - Xi-chuan ZHOU
A1 - Hai-bin SHEN
J0 - Journal of Zhejiang University Science A
VL - 10
IS - 4
SP - 504
EP - 511
%@ 1673-565X
Y1 - 2009
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0820221

In standard canonical correlation analysis (CCA), the data from definite datasets are used to estimate their canonical correlation. In real applications, for example in bilingual text retrieval, it may have a great portion of data that we do not know which set it belongs to. This part of data is called unlabeled data, while the rest from definite datasets is called labeled data. We propose a novel method called regularized canonical correlation analysis (RCCA), which makes use of both labeled and unlabeled samples. Specifically, we learn to approximate canonical correlation as if all data were labeled. Then, we describe a generalization of RCCA for the multi-set situation. Experiments on four real world datasets, Yeast, Cloud, Iris, and Haberman, demonstrate that, by incorporating the unlabeled data points, the accuracy of correlation coefficients can be improved by over 30%.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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