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DisSAGD: A Distributed Parameter Update Scheme Based on Variance Reduction
Machine learning models often converge slowly and are unstable due to the significant variance of random data when using a sample estimate gradient in SGD. To increase the speed of convergence and improve stability, a distributed SGD algorithm based on variance reduction, named DisSAGD, is proposed...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8347539/ https://www.ncbi.nlm.nih.gov/pubmed/34372361 http://dx.doi.org/10.3390/s21155124 |