Semi-paired Probabilistic Canonical Correlation Analysis - Intelligent Information Processing VII (IIP 2014) Access content directly
Conference Papers Year : 2014

Semi-paired Probabilistic Canonical Correlation Analysis


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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hal-01383310 , version 1 (18-10-2016)





Bo Zhang, Jie Hao, Gang Ma, Jinpeng Yue, Zhongzhi Shi. Semi-paired Probabilistic Canonical Correlation Analysis. 8th International Conference on Intelligent Information Processing (IIP), Oct 2014, Hangzhou, China. pp.1-10, ⟨10.1007/978-3-662-44980-6_1⟩. ⟨hal-01383310⟩
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