Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis.

IEEE Transactions on Signal Processing(2017)

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摘要
Generalized canonical correlation analysis (GCCA) aims at finding latent low-dimensional common structure from multiple views (feature vectors in different domains) of the same entities. Unlike principal component analysis that handles a single view, (G)CCA is able to integrate information from different feature spaces. Here we focus on MAX-VAR GCCA, a popular formulation that has recently gained ...
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关键词
Correlation,Algorithm design and analysis,Convergence,Scalability,Optimization,Signal processing algorithms,Principal component analysis
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