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A self-organizing principle for learning nonlinear manifolds

Modern science confronts us with massive amounts of data: expression profiles of thousands of human genes, multimedia documents, subjective judgments on consumer products or political candidates, trade indices, global climate patterns, etc. These data are often highly structured, but that structure...

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Detalhes bibliográficos
Main Authors: Agrafiotis, Dimitris K., Xu, Huafeng
Formato: Artigo
Idioma:Inglês
Publicado em: National Academy of Sciences 2002
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC138530/
https://ncbi.nlm.nih.gov/pubmed/12444256
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.242424399
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