Damped Newton Stochastic Gradient Descent Method for Neural Networks Training

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...

書誌詳細
主要な著者:	Jingcheng Zhou, Wei Wei, Ruizhi Zhang, Zhiming Zheng
フォーマット:	論文
言語:	English
出版事項:	MDPI AG 2021-06-01
シリーズ:	Mathematics
主題:	stochastic gradient descent damped Newton convexity
オンライン･アクセス:	https://www.mdpi.com/2227-7390/9/13/1533

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