Itao: a new iterative thresholding algorithm based optimizer for deep neural networks

In this paper, we propose a new iterative thresholding algorithm based optimizer (Itao) for deep neural networks. It is a first-order gradient-based algorithm with Tikhonov regularization for stochastic objective functions. It is fast and straightforward to implement. It acts on the parameters and t...

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Veröffentlicht in:	IEEE access Jg. 10; S. 1
Hauptverfasser:	Merrouchi, M., Atifi, K., Skittou, M., T.Gadi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Artificial neural networks Back propagation Back propagation networks Deep learning Inverse problems Iterative algorithms Iterative methods Iterative thresholding algorithm based optimizer (Itao) Linear programming Machine learning Mathematical models Neural networks Optimization optimizer algorithm Parameters Regularization Robustness (mathematics) Training
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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