A further study on the inequality constraints in stochastic configuration networks

DOI10.1016/j.ins.2019.02.066zbMath1451.68238OpenAlexW2921936057WikidataQ128279523 ScholiaQ128279523MaRDI QIDQ2215130

Ruiqiang He, Xixi Jia, Wei-wei Wang, Xiang Chu Feng, Xiao-Long Zhu

Publication date: 10 December 2020

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

Full work available at URL: https://doi.org/10.1016/j.ins.2019.02.066

zbMATH Keywords

inequality constraintsdata modelingstochastic configuration networksrandomized learning

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Learning and adaptive systems in artificial intelligence (68T05) Probabilistic graphical models (62H22)

Related Items (1)

Stochastic configuration networks with chaotic maps and hierarchical learning strategy

Cites Work

• Multilayer feedforward networks are universal approximators
• Insights into randomized algorithms for neural networks: practical issues and common pitfalls
• A class-modular feedforward neural network for handwriting recognition

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