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Non-iterative and Fast Deep Learning: Multilayer Extreme Learning Machines
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Metadata
- Authors
- Zhang, J., Li, Y., Xiao, W., & Zhang, Z.
- Affiliations
- Peking University (CN)
- Beijing Institute of Technology (CN)
- University of Science and Technology Beijing (CN)
- University of Leeds (GB)
- Corresponding author
- Xiao, Wendong
- Venue
- Journal of the Franklin Institute
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 357
- Issue
- 13
- Pages
- 8925-8955
- ISSN
- 0016-0032 (ISSN-L)
- OpenAlex
- W3040832198
- Cited by
- 179
- References
- 146
- Citations by year
- 2026: 6 · 2025: 14 · 2024: 22 · 2023: 83 · 2022: 35 · 2021: 17 · 2020: 2
- FWCI
- 13.46
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the Franklin Institute (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Ministry of Science and Technology of the People's Republic of China
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and ELM
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Stochastic Gradient Optimization Techniques
- Keywords
- extreme learning machine, random neural networks, universal approximation, deep learning training efficiency
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