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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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| Publicado no: | Entropy (Basel) |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7515077/ https://ncbi.nlm.nih.gov/pubmed/33267302 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e21060588 |
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