articleTop 1% cited
Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings
Neural Networks · 1990 · Vol. 3(5) · pp. 535–549
Halbert White✉(University of California, San Diego)
Face and Expression RecognitionNeural Networks and ApplicationsComplex Network Analysis TechniquesEstimatorConsistency (knowledge bases)Feed forwardArtificial neural networkComputer scienceMean squared errorNonparametric regressionAlgorithmFeature (linguistics)Feedforward neural network
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679
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References
On the approximate realization of continuous mappings by neural networks
Neural Networks · 1989 · 4,195 citations
Introductory Real Analysis.
American Mathematical Monthly · 1971 · 1,418 citations
Learning in Artificial Neural Networks: A Statistical Perspective
Neural Computation · 1989 · 920 citations
Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks
Neural Networks · 1990 · 2,101 citations
Cross-Validatory Choice and Assessment of Statistical Predictions
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1974 · 10,283 citations
Multilayer feedforward networks are universal approximators
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