An Adaptive Deep Learning Optimization Method Based on Radius of Curvature
An adaptive clamping method (SGD-MS) based on the radius of curvature is designed to alleviate the local optimal oscillation problem in deep neural network, which combines the radius of curvature of the objective function and the gradient descent of the optimizer. The radius of curvature is consider...
Guardado en:
Autores principales: | Jiahui Zhang, Xinhao Yang, Ke Zhang, Chenrui Wen |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Hindawi Limited
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/acab22f5e532433c807e6c5f9bb9d3fc |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Feasibility of the deep learning method for estimating the ventilatory threshold with electrocardiography data
por: Kotaro Miura, et al.
Publicado: (2020) -
Utilization of Nursing Defect Management Evaluation and Deep Learning in Nursing Process Reengineering Optimization
por: Yue Liu, et al.
Publicado: (2021) -
Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data
por: Yu Wang, et al.
Publicado: (2021) -
Scalable and accurate deep learning with electronic health records
por: Alvin Rajkomar, et al.
Publicado: (2018) -
Deep learning-enabled medical computer vision
por: Andre Esteva, et al.
Publicado: (2021)