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Online Gradient Descent for Kernel-Based Maximum Correntropy Criterion
In the framework of statistical learning, we study the online gradient descent algorithm generated by the correntropy-induced losses in Reproducing kernel Hilbert spaces (RKHS). As a generalized correlation measurement, correntropy has been widely applied in practice, owing to its prominent merits o...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515137/ https://www.ncbi.nlm.nih.gov/pubmed/33267358 http://dx.doi.org/10.3390/e21070644 |