Improving Deep Neural Networks' Training for Image Classification With Nonlinear Conjugate Gradient-Style Adaptive Momentum

Momentum is crucial in stochastic gradient-based optimization algorithms for accelerating or improving training deep neural networks (DNNs). In deep learning practice, the momentum is usually weighted by a well-calibrated constant. However, tuning the hyperparameter for momentum can be a significant...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 35; H. 9; S. 12288 - 12300
Hauptverfasser:	Wang, Bao, Ye, Qiang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.09.2024
Schlagworte:	Adaptive momentum Classification algorithms Convergence Deep learning Image classification nonlinear conjugate gradient (NCG) Robustness Stochastic processes Training
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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