This paper aims at proposing the joint use of Canonical Correlation Analysis and Procrustes Rotations (RCA), when we deal with a text and its translation into another language. The basic idea is representing words in the two different natural languages on a common reference space. The main characteristic of this space is to be language independent, although Procrustes Rotation is performed tran...

Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are well known techniques for face recognition. Both PCA and LDA by themselves have good recognition rates. We propose Canonical Correlation Analysis (CCA) for combining two feature extractors to improve the performance of the system, by obtaining the advantages of both. CCA finds the transformation for each extractor dat...

We present a fast algorithm for approximate canonical correlation analysis (CCA). Given a pair of tall-and-thin matrices, the proposed algorithm first employs a randomized dimensionality reduction transform to reduce the size of the input matrices, and then applies any CCA algorithm to the new pair of matrices. The algorithm computes an approximate CCA to the original pair of matrices with prov...

Capturing and analyzing the correlations among facial parts are important for interpreting facial behaviors precisely. In this paper, we exploit Canonical Correlation Analysis (CCA) to model the correlations of facial parts for facial expression analysis. We propose a Matrix-based Canonical Correlation Analysis (MCCA) for better correlation analysis on 2D image or matrix data in general. Extens...

In financial distress studies selection of variable is commonly basedon the success of variables in variable sets employed in earlierbankruptcy studies, suggestions in the literature or an accompanyingdata reduction in a large set of variables. If seemingly different variablesets exhibit a strong relationship then heterogeneous variable setscapture common information. Canonical correlation anal...

the purpose of this research was to investigate the relationship between emotional intelligence and academic performance evaluation. the population of the study included faculty members of the university of urmia in 1391. to select a sample, stratified random sampling method was used while considering the proportions. in total, 200 people were selected. the study was of descriptive - correlatio...

To date, the massive quantity of data generated by high-throughput techniques has not yet met bioinformatics treatment required to make full use of it. This is partially due to a mismatch in experimental and analytical study design but primarily due to a lack of adequate analytical approaches. When integrating multiple data types e.g. transcriptomics and metabolomics, multidimensional statistic...

This paper investigated the organization of the postural control system in human upright stance. To this aim the shared variance between joint and 3D total body center of mass (COM) motions was analyzed using multivariate canonical correlation analysis (CCA). The CCA was performed as a function of established models of postural control that varied in their joint degrees of freedom (DOF), namely...

For the problem of low recognition rate on low resolution face images, a super-resolution method for face recognition based on correlated features and nonlinear mappings is proposed in this paper. Canonical correlation analysis (CCA) is applied to establish the correlated subspaces between the features of high and low resolution face images, and radial base functions (RBFs) are employed to cons...

Multiview LSA (MVLSA) is a generalization of Latent Semantic Analysis (LSA) that supports the fusion of arbitrary views of data and relies on Generalized Canonical Correlation Analysis (GCCA). We present an algorithm for fast approximate computation of GCCA, which when coupled with methods for handling missing values, is general enough to approximate some recent algorithms for inducing vector r...