Convergence of an online gradient method for feedforward neural networks with stochastic inputs.

DOI10.1016/J.CAM.2003.08.062zbMath1062.68101OpenAlexW2167777352MaRDI QIDQ1427233

Wei Wu, Yulong Tian, Zheng-xue Li

Publication date: 14 March 2004

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2003.08.062

zbMATH Keywords

ConvergenceFeedforward neural networksOnline gradient methodStochastic inputs

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) General topics in artificial intelligence (68T01)

Related Items (3)

Convergence analysis of online gradient method for BP neural networks ⋮ Convergence analyses on sparse feedforward neural networks via group lasso regularization ⋮ An online gradient method with momentum for two-layer feedforward neural networks

Cites Work

• Training multilayer perceptrons via minimization of sum of ridge functions
• Deterministic convergence of an online gradient method for neural networks
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