Damped Newton Stochastic Gradient Descent Method for Neural Networks Training
First-order methods such as stochastic gradient descent (SGD) have recently become popular optimization methods to train deep neural networks (DNNs) for good generalization; however, they need a long training time. Second-order methods which can lower the training time are scarcely used on account o...
Үндсэн зохиолчид: | Jingcheng Zhou, Wei Wei, Ruizhi Zhang, Zhiming Zheng |
---|---|
Формат: | Өгүүллэг |
Хэл сонгох: | English |
Хэвлэсэн: |
MDPI AG
2021-06-01
|
Цуврал: | Mathematics |
Нөхцлүүд: | |
Онлайн хандалт: | https://www.mdpi.com/2227-7390/9/13/1533 |
Ижил төстэй зүйлс
Ижил төстэй зүйлс
-
Adaptive Stochastic Gradient Descent Method for Convex and Non-Convex Optimization
-н: Ruijuan Chen, зэрэг
Хэвлэсэн: (2022-11-01) -
The Improved Stochastic Fractional Order Gradient Descent Algorithm
-н: Yang Yang, зэрэг
Хэвлэсэн: (2023-08-01) -
Recent Advances in Stochastic Gradient Descent in Deep Learning
-н: Yingjie Tian, зэрэг
Хэвлэсэн: (2023-01-01) -
A Geometric Interpretation of Stochastic Gradient Descent Using Diffusion Metrics
-н: Rita Fioresi, зэрэг
Хэвлэсэн: (2020-01-01) -
Stochastic gradient descent with random label noises: doubly stochastic models and inference stabilizer
-н: Haoyi Xiong, зэрэг
Хэвлэсэн: (2024-01-01)