Efficient extreme learning machine via very sparse random projection

DOI10.1007/s00500-018-3128-7zbMath1398.68433OpenAlexW2792300954MaRDI QIDQ1797950

Chuangquan Chen, Chi-Man Vong, Weiru Wang, Chi-Man Wong, Pak-Kin Wong

Publication date: 22 October 2018

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-018-3128-7

zbMATH Keywords

dimension reductionextreme learning machine (ELM)compression layersparse-Bernoulli matrixvery sparse random projection

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Jointly evolving and compressing fuzzy system for feature reduction and classification

Uses Software

• UCI-ml
• OP-ELM
• OpenML
• R3P-Loc

Cites Work

• Unnamed Item
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• Decoding by Linear Programming
• Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
• The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network
• Random Projections for Large-Scale Regression
• Learning representations by back-propagating errors

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