Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing

Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple...

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Detalles Bibliográficos
Autores principales: Li, Shuang, Liu, Bing, Zhang, Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4876218/
https://www.ncbi.nlm.nih.gov/pubmed/27247562
http://dx.doi.org/10.1155/2016/4920670

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4876218/
https://www.ncbi.nlm.nih.gov/pubmed/27247562
http://dx.doi.org/10.1155/2016/4920670

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