Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality in Approximation on Hölder Class

DOI10.1137/21m144431xarXiv2103.00542OpenAlexW4385985820MaRDI QIDQ6137593

Xiliang Lu, Fengru Wang, Yan-Ming Lai, Yuan-Yuan Yang, Jerry Zhijian Yang, Yu Ling Jiao

Publication date: 4 September 2023

Published in: SIAM Journal on Mathematical Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2103.00542

zbMATH Keywords

approximationHölder continuous functioncurse of dimensionalitydeep neural network

Mathematics Subject Classification ID

Multidimensional problems (41A63) Algorithms for approximation of functions (65D15) Approximation by other special function classes (41A30)

Related Items (1)

Analysis of the rate of convergence of two regression estimates defined by neural features which are easy to implement

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