A global universality of two-layer neural networks with ReLU activations

DOI10.1155/2021/6637220zbMath1480.41006arXiv2011.10225OpenAlexW3200344735MaRDI QIDQ2236407

Yoshihiro Sawano, Isao Ishikawa, Masahiro Ikeda, Naoya Hatano

Publication date: 22 October 2021

Published in: Journal of Function Spaces (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2011.10225

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Approximation by other special function classes (41A30) Networks and circuits as models of computation; circuit complexity (68Q06)

Related Items (2)

Heaviside function as an activation function ⋮ Universality of neural networks with a sigmoidal activation or discriminatory functions on functional Banach lattices over the real line

Cites Work

• Unnamed Item
• Multilayer feedforward networks are universal approximators
• Neural network with unbounded activation functions is universal approximator
• Approximation by superpositions of a sigmoidal function

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