A convergence analysis of Nesterov's accelerated gradient method in training deep linear neural networks

DOI10.1016/J.INS.2022.08.090arXiv2204.08306OpenAlexW4224273755WikidataQ114167234 ScholiaQ114167234MaRDI QIDQ6125246

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Publication date: 11 April 2024

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

Full work available at URL: https://arxiv.org/abs/2204.08306

zbMATH Keywords

Nesterov's accelerated gradient methodover-parameterizationdeep linear neural network

Mathematics Subject Classification ID

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

Cites Work

• Some NP-complete problems in quadratic and nonlinear programming
• Effects of depth, width, and initialization: A convergence analysis of layer-wise training for deep linear neural networks
• Convergence analysis of AdaBound with relaxed bound functions for non-convex optimization

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