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- Kernel-independent_component_analysis abstract "In statistics, kernel-independent component analysis (kernel ICA) is an efficient algorithm for independent component analysis which estimates source components by optimizing a generalized variance contrast function, which is based on representations in a reproducing kernel Hilbert space. Those contrast functions use the notion of mutual information as a measure of statistical independence.".
- Kernel-independent_component_analysis wikiPageID "48312994".
- Kernel-independent_component_analysis wikiPageLength "3558".
- Kernel-independent_component_analysis wikiPageOutDegree "8".
- Kernel-independent_component_analysis wikiPageRevisionID "702877924".
- Kernel-independent_component_analysis wikiPageWikiLink Category:Statistical_algorithms.
- Kernel-independent_component_analysis wikiPageWikiLink Independence_(probability_theory).
- Kernel-independent_component_analysis wikiPageWikiLink Independent_component_analysis.
- Kernel-independent_component_analysis wikiPageWikiLink Reproducing_kernel_Hilbert_space.
- Kernel-independent_component_analysis wikiPageWikiLink Whitening_transformation.
- Kernel-independent_component_analysis wikiPageWikiLinkText "Kernel-independent component analysis".
- Kernel-independent_component_analysis wikiPageWikiLinkText "kernel-independent component analysis".
- Kernel-independent_component_analysis wikiPageUsesTemplate Template:Reflist.
- Kernel-independent_component_analysis wikiPageUsesTemplate Template:Statistics-stub.
- Kernel-independent_component_analysis subject Category:Statistical_algorithms.
- Kernel-independent_component_analysis hypernym Algorithm.
- Kernel-independent_component_analysis type Software.
- Kernel-independent_component_analysis comment "In statistics, kernel-independent component analysis (kernel ICA) is an efficient algorithm for independent component analysis which estimates source components by optimizing a generalized variance contrast function, which is based on representations in a reproducing kernel Hilbert space. Those contrast functions use the notion of mutual information as a measure of statistical independence.".
- Kernel-independent_component_analysis label "Kernel-independent component analysis".
- Kernel-independent_component_analysis wasDerivedFrom Kernel-independent_component_analysis?oldid=702877924.
- Kernel-independent_component_analysis isPrimaryTopicOf Kernel-independent_component_analysis.