Canonical correlation analysis results
Canonical Correlation Analysis
... a canonical variate by the other canonical variate) and the correlation between the two ...individual analysis, all three leadership styles are shown to reduce ...the results indicate ...
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Bayesian Canonical Correlation Analysis
... picted in the chromosomal order (x-axis), with BIBFA (red) and the window-based com- parison method of pint (blue). Since the gene detection is based on the ranks of the genes, the two weight vectors have here been ...
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Sufficient Canonical Correlation Analysis
... Sufficient Canonical Correlation Analysis Yiwen Guo, Xiaoqing Ding, Fellow, IEEE, Changsong Liu, Member, IEEE, and Jing-Hao Xue Abstract—Canonical correlation analysis (CCA) is ...
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Representation-Constrained Canonical Correlation Analysis: A Hybridization of Canonical Correlation and Principal Component Analyses
... interpretation of empirical results rather hazardous. One may easily be misled to a conclusion that such two datasets are highly correlated while the truth may be quite far from it. II. Objectives of the Present ...
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Representation Constrained Canonical Correlation Analysis: A Hybridization of Canonical Correlation and Principal Component Analyses
... interpretation of empirical results rather hazardous. One may easily be misled to a conclusion that such two datasets are highly correlated while the truth may be quite far from it. II. Objectives of the Present ...
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Canonical Correlation Analysis for Longitudinal Data
... In this dissertation, we provide theory and application of CCA to repeatedly observed (over a time period) data on two sets of variables. The data here look like data on a multivariate time series, but the interest is to ...
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Sparse Kernel Canonical Correlation Analysis
... Empirical results show that SKCCA not only performs well in computing sparse dual transformations, but also alleviates the over-fitting problem of kernel ...
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Deep Generalized Canonical Correlation Analysis
... We learned PCA, GCCA, and WGCCA represen- tations of width r ∈ [10, 1000], and select embed- dings based on development set R@1K. There are several points to note: First is that DGCCA outperforms linear methods at ...
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Multicollinearity in canonical correlation analysis in maize.
... the canonical correlations without elimination of variables were greater than those with elimination of ...estimated canonical coefficients can assume absurd values without any coherence with the biological ...
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Robust sparse canonical correlation analysis
... the Canonical Ridge. The Canonical Ridge performs regularization, but the canonical vectors produced by the Canonical Ridge are not ...two canonical variate pairs are extracted using ...
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Robust sparse canonical correlation analysis
... the results from the “Uncorrelated Sparse Low-dimensional” ...method results in increased estimation accuracy when the true canonical vectors have a sparse ...
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Generalized canonical correlation analysis with missing values
... Generalized canonical correlation analysis is a versatile technique that allows the joint analysis of several sets of data ...generalized canonical correlation analysis ...
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Canonical Correlation Analysis in Cross-Domain Recommendation
... algorithms on these domain pairs. To better comprehend the difference between algorithms, we order the domain pairs based on RMSE and MAE of CD-CCA algorithm on them. Due to the visualization limitations, we cannot show ...
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Statistical Consistency of Kernel Canonical Correlation Analysis
... component analysis (ICA), since Bach and Jordan (2002) use kernel CCA in their kernel ICA ...theoretical results developed in this paper will work as a basis for analyzing the properties of the kernel ICA ...
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Matrix-Variate Probabilistic Model for Canonical Correlation Analysis
... (iv) Extending the model into supervised or semi super- vised cases [5]. One major drawback of aforementioned methods is that they only work for data vectors while in computer vision research, samples are often ...
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Classification of Crystallographic Data Using Canonical Correlation Analysis
... quantitative analysis performed by the Ri- etveld ...the results of CCA analysis (middle parts) obtained by the different spatial mod- els of Figure 5, and standard quantitative analysis ...
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Informative Data Fusion: Beyond Canonical Correlation Analysis
... recent results from RMT [84, 85, 86] to precisely quantify the accuracy of the subspace ...performance analysis of the stochastic and deterministic ...
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Multi-View Regression via Canonical Correlation Analysis
... The remainder of the paper is organized as follows. Section 2 formalizes our multi-view assumption and reviews CCA. Section 3 presents the main results, where the bias-variance tradeoff and the intrinsic ...
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Person re-identification by robust canonical correlation analysis
... To compare our method with the state-of-the-art, 16 recent methods are included in the comparison on the VIPeR dataset. The matching rates at various ranks for different methods are reported in Table I. Compared to the ...
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Canonical correlation analysis for gene-based pleiotropy discovery.
... In Table 2 we show some of the most important pleiotropic genotype/multiple phenotype associations, including the p-value of CCA association and the phenotypes with which they are associated. We also show Fisher’s ...
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