In recent years, the advances in data collection and statistical analysis promotes canonical
correlation analysis (CCA) available for more advanced research. CCA is the main …

Canonical correlation analysis is a family of multivariate statistical methods for the analysis
of paired sets of variables. Since its proposition, canonical correlation analysis has, for …

Canonical correlation analysis (CCA) and partial least squares (PLS) are well-known
techniques for feature extraction from two sets of multidimensional variables. The …

Abstract Canonical Correlation Analysis (CCA) is a widely used spectral technique for
finding correlation structures in multi-view datasets. In this paper, we tackle the problem of …

In this paper, we study canonical correlation analysis (CCA), which is a powerful tool in
multivariate data analysis for finding the correlation between two sets of multidimensional …

As a dimension reduction algorithm, canonical correlation analysis (CCA) encounters the
issue of selecting the number of canonical correlations. In this letter, we present a Bayesian …

Canonical correlation analysis (CCA) is a classical representation learning technique for
finding correlated variables in multi-view data. Several nonlinear extensions of the original …

Canonical correlation analysis (CCA) is a classical method for seeking correlations between
two multivariate data sets. During the last ten years, it has received more and more attention …

Canonical correlation analysis (CCA) is a popular and powerful dimensionality reduction
method to analyze paired multi-view data. However, when facing semi-paired and semi …

Canonical Correlation Analysis (CCA) is a well-known technique for finding the correlations
between two sets of multi-dimensional variables. It projects both sets of variables into a …