A zeroing neural dynamics based acceleration optimization approach for optimizers in deep neural networks

DOI10.1016/j.neunet.2022.03.010OpenAlexW4220705768MaRDI QIDQ6072593

Shubin Li, Haoen Huang, Shan Liao, Jiayong Liu, Xiuchun Xiao

Publication date: 13 October 2023

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2022.03.010

zbMATH Keywords

optimizationoptimizerzeroing neural dynamics (ZND)deep neural networks (DNN)

Mathematics Subject Classification ID

Artificial intelligence (68Txx)

Related Items (1)

Distributed time-varying optimization control protocol for multi-agent systems via finite-time consensus approach

Cites Work

• Unnamed Item
• Unnamed Item
• Discrete-time noise-tolerant Zhang neural network for dynamic matrix pseudoinversion
• Hybrid tensor decomposition in neural network compression
• Analytical convergence regions of accelerated gradient descent in nonconvex optimization under regularity condition
• Robust PD-type iterative learning control for discrete systems with multiple time-delays subjected to polytopic uncertainty and restricted frequency-domain
• A parallel computing method based on zeroing neural networks for time-varying complex-valued matrix Moore-Penrose inversion
• Noise-Tolerant ZNN Models for Solving Time-Varying Zero-Finding Problems: A Control-Theoretic Approach
• Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints
• Analysis of Optimization Algorithms via Integral Quadratic Constraints: Nonstrongly Convex Problems
• NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm
• A Stochastic Approximation Method
• Convergence of the RMSProp deep learning method with penalty for nonconvex optimization
• A fast saddle-point dynamical system approach to robust deep learning

This page was built for publication: A zeroing neural dynamics based acceleration optimization approach for optimizers in deep neural networks