Kernel Risk-Sensitive Mean p-Power Error Algorithms for Robust Learning

As a nonlinear similarity measure defined in the reproducing kernel Hilbert space (RKHS), the correntropic loss (C-Loss) has been widely applied in robust learning and signal processing. However, the highly non-convex nature of C-Loss results in performance degradation. To address this issue, a conv...

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Detalles Bibliográficos
Autores principales: Zhang, Tao, Wang, Shiyuan, Zhang, Haonan, Xiong, Kui, Wang, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515077/
https://www.ncbi.nlm.nih.gov/pubmed/33267302
http://dx.doi.org/10.3390/e21060588

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515077/
https://www.ncbi.nlm.nih.gov/pubmed/33267302
http://dx.doi.org/10.3390/e21060588

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