Add to ORKG• Coefficients are mostly zeros and the computational complexity is high • Inspired by [3], a new L0 norm regularized algorithm: A Sparse extension to the KCCA algorith
Canonical Correlation Analysis (CCA) is a multivariate technique that takes two datasets and forms t...
Abstract. Canonical correlation analysis (CCA) is a classical multivariate method concerned with des...
Summary. Sparse Canonical Correlation Analysis (CCA) has received considerable atten-tion in high-di...
This paper presents gradKCCA, a large-scale sparse non-linear canonical correlation method. Like Ker...
AbstractKernel canonical correlation analysis (KCCA) is a procedure for assessing the relationship b...
[Background]Advance in high-throughput technologies in genomics, transcriptomics, and metabolomics h...
Abstract. Kernel canonical correlation analysis (KCCA) is a dimen-sionality reduction technique for ...
In this paper, an orthogonal regularized kernel canonical correlation analysis algorithm (ORKCCA) is...
International audienceAn efficient projection enforcing both normalization and sparsity is proposed ...
Kernel canonical correlation analysis (KCCA) is a dimensionality reduction technique for paired data...
Canonical correlation analysis (CCA) describes the associations between two sets of variables by max...
International audienceThere is a growing need to analyze datasets characterized by several sets of v...
Dimensionality reduction is ubiquitous in biomedical applications. A newly proposed spectral dimensi...
Canonical correlation analysis (CCA) is a multivariate statistical method which describes the associ...
We introduce Deep Canonical Correlation Analysis (DCCA), a method to learn com-plex nonlinear transf...
Canonical Correlation Analysis (CCA) is a multivariate technique that takes two datasets and forms t...
Abstract. Canonical correlation analysis (CCA) is a classical multivariate method concerned with des...
Summary. Sparse Canonical Correlation Analysis (CCA) has received considerable atten-tion in high-di...
This paper presents gradKCCA, a large-scale sparse non-linear canonical correlation method. Like Ker...
AbstractKernel canonical correlation analysis (KCCA) is a procedure for assessing the relationship b...
[Background]Advance in high-throughput technologies in genomics, transcriptomics, and metabolomics h...
Abstract. Kernel canonical correlation analysis (KCCA) is a dimen-sionality reduction technique for ...
In this paper, an orthogonal regularized kernel canonical correlation analysis algorithm (ORKCCA) is...
International audienceAn efficient projection enforcing both normalization and sparsity is proposed ...
Kernel canonical correlation analysis (KCCA) is a dimensionality reduction technique for paired data...
Canonical correlation analysis (CCA) describes the associations between two sets of variables by max...
International audienceThere is a growing need to analyze datasets characterized by several sets of v...
Dimensionality reduction is ubiquitous in biomedical applications. A newly proposed spectral dimensi...
Canonical correlation analysis (CCA) is a multivariate statistical method which describes the associ...
We introduce Deep Canonical Correlation Analysis (DCCA), a method to learn com-plex nonlinear transf...
Canonical Correlation Analysis (CCA) is a multivariate technique that takes two datasets and forms t...
Abstract. Canonical correlation analysis (CCA) is a classical multivariate method concerned with des...
Summary. Sparse Canonical Correlation Analysis (CCA) has received considerable atten-tion in high-di...