KernelICA-package: KernelICA-package
In KernelICA: Kernel Independent Component Analysis
Description
Author(s)
References
Description
The kernel independent component analysis (kernel ICA) method introduced by Bach and Jordan in 2002 (see references).
The incomplete Cholesky decomposition used in kernel ICA is provided as separate function.
Author(s)
Christoph L. Koesner
Klaus Nordhausen
Maintainer: Christoph L. Koesner <christoph@koesner.at>
References
Francis R. Bach, Michael I. Jordan
Kernel independent component analysis
Journal of Machine Learning Research 2002
doi: 10.1162/153244303768966085
Francis R. Bach, Michael I. Jordan
Predictive low-rank decomposition for kernel methods.
Proceedings of the Twenty-second International Conference on Machine Learning (ICML) 2005
doi: 10.1145/1102351.1102356.
Sean Martin, Andrew M. Raim, Wen Huang, Kofi P. Adragni
ManifoldOptim: An R Interface to the ROPTLIB Library for Riemannian Manifold Optimization
Journal of Statistical Software 2020
doi: 10.18637/jss.v093.i01
KernelICA documentation built on March 1, 2021, 5:08 p.m.
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Description Author(s) References
Description
The kernel independent component analysis (kernel ICA) method introduced by Bach and Jordan in 2002 (see references). The incomplete Cholesky decomposition used in kernel ICA is provided as separate function.
Author(s)
Christoph L. Koesner
Klaus Nordhausen
Maintainer: Christoph L. Koesner <christoph@koesner.at>
References
Francis R. Bach, Michael I. Jordan
Kernel independent component analysis
Journal of Machine Learning Research 2002
doi: 10.1162/153244303768966085
Francis R. Bach, Michael I. Jordan
Predictive low-rank decomposition for kernel methods.
Proceedings of the Twenty-second International Conference on Machine Learning (ICML) 2005
doi: 10.1145/1102351.1102356.
Sean Martin, Andrew M. Raim, Wen Huang, Kofi P. Adragni
ManifoldOptim: An R Interface to the ROPTLIB Library for Riemannian Manifold Optimization
Journal of Statistical Software 2020
doi: 10.18637/jss.v093.i01
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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