Semi-paired Probabilistic Canonical Correlation Analysis

Abstract : CCA is a powerful tool for analyzing paired multi-view data. However, when facing semi-paired multi-view data which widely exist in real-world problems, CCA usually performs poorly due to its requirement of data pairing between different views in nature. To cope with this problem, we propose a semi-paired variant of CCA named SemiPCCA based on the probabilistic model for CCA. Experiments with artificially generated samples demonstrate the effectiveness of the proposed method.
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Communication dans un congrès
Zhongzhi Shi; Zhaohui Wu; David Leake; Uli Sattler. 8th International Conference on Intelligent Information Processing (IIP), Oct 2014, Hangzhou, China. Springer, IFIP Advances in Information and Communication Technology, AICT-432, pp.1-10, 2014, Intelligent Information Processing VII. 〈10.1007/978-3-662-44980-6_1〉
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Soumis le : mardi 18 octobre 2016 - 14:51:42
Dernière modification le : vendredi 3 novembre 2017 - 22:24:06

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Bo Zhang, Jie Hao, Gang Ma, Jinpeng Yue, Zhongzhi Shi. Semi-paired Probabilistic Canonical Correlation Analysis. Zhongzhi Shi; Zhaohui Wu; David Leake; Uli Sattler. 8th International Conference on Intelligent Information Processing (IIP), Oct 2014, Hangzhou, China. Springer, IFIP Advances in Information and Communication Technology, AICT-432, pp.1-10, 2014, Intelligent Information Processing VII. 〈10.1007/978-3-662-44980-6_1〉. 〈hal-01383310〉

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