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Literature DB >> 11195936

Kernel and nonlinear canonical correlation analysis.

Abstract

We review a neural implementation of the statistical technique of Canonical Correlation Analysis (CCA) and extend it to nonlinear CCA. We then derive the method of kernel-based CCA and compare these two methods on real and artificial data sets before using both on the Blind Separation of Sources.

Mesh：

Year: 2000 PMID： 11195936 DOI： 10.1142/S012906570000034X

Source DB: PubMed Journal: Int J Neural Syst ISSN： 0129-0657 Impact factor: 5.866

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Cited

12 in total

1. LOCAL KERNEL CANONICAL CORRELATION ANALYSIS WITH APPLICATION TO VIRTUAL DRUG SCREENING.

Authors: Daniel Samarov; J S Marron; Yufeng Liu; Christopher Grulke; Alexander Tropsha
Journal: Ann Appl Stat Date: 2011-09-01 Impact factor: 2.083

2. A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.

Authors: Mehmet Gönen; Barbara A Weir; Glenn S Cowley; Francisca Vazquez; Yuanfang Guan; Alok Jaiswal; Masayuki Karasuyama; Vladislav Uzunangelov; Tao Wang; Aviad Tsherniak; Sara Howell; Daniel Marbach; Bruce Hoff; Thea C Norman; Antti Airola; Adrian Bivol; Kerstin Bunte; Daniel Carlin; Sahil Chopra; Alden Deran; Kyle Ellrott; Peddinti Gopalacharyulu; Kiley Graim; Samuel Kaski; Suleiman A Khan; Yulia Newton; Sam Ng; Tapio Pahikkala; Evan Paull; Artem Sokolov; Hao Tang; Jing Tang; Krister Wennerberg; Yang Xie; Xiaowei Zhan; Fan Zhu; Tero Aittokallio; Hiroshi Mamitsuka; Joshua M Stuart; Jesse S Boehm; David E Root; Guanghua Xiao; Gustavo Stolovitzky; William C Hahn; Adam A Margolin
Journal: Cell Syst Date: 2017-10-04 Impact factor: 10.304

Kernel and nonlinear canonical correlation analysis.

1. LOCAL KERNEL CANONICAL CORRELATION ANALYSIS WITH APPLICATION TO VIRTUAL DRUG SCREENING.

2. A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.

Review 3. Multi-omic and multi-view clustering algorithms: review and cancer benchmark.

4. Joint sparse canonical correlation analysis for detecting differential imaging genetics modules.

5. Canonical correlation analysis for gene-based pleiotropy discovery.

6. Kernel Manifold Alignment for Domain Adaptation.

7. Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images.

8. Nonlinear Canonical Correlation Analysis:A Compressed Representation Approach.

Review 9. Microbiome Multi-Omics Network Analysis: Statistical Considerations, Limitations, and Opportunities.

10. Kernel methods and their derivatives: Concept and perspectives for the earth system sciences.