A backpropagation learning algorithm with graph regularization for feedforward neural networks

DOI10.1016/j.ins.2022.05.121OpenAlexW4281728148WikidataQ114951083 ScholiaQ114951083MaRDI QIDQ6195182

Wenyu Yang, Yetian Fan

Publication date: 13 March 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2022.05.121

zbMATH Keywords

convergenceneural networkbackpropagationgraph regularization

Mathematics Subject Classification ID

Biology and other natural sciences (92-XX) Computer science (68-XX)

Cites Work

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• Batch gradient method with smoothing \(L_{1/2}\) regularization for training of feedforward neural networks
• A modified gradient-based neuro-fuzzy learning algorithm and its convergence
• Connectionist learning of belief networks
• A Penalty-Function Approach for Pruning Feedforward Neural Networks
• The Group Lasso for Logistic Regression
• Learning representations by back-propagating errors

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