Approximation of functions from korobov spaces by deep convolutional neural networks

DOI10.1007/s10444-022-09991-xOpenAlexW4310837332MaRDI QIDQ2108977

Yanyan Li

Publication date: 20 December 2022

Published in: Advances in Computational Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10444-022-09991-x

zbMATH Keywords

curse of dimensionalitymachine learningdeep convolutional neural networkskorobov spaces

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Rate of convergence, degree of approximation (41A25)

Related Items (2)

Rates of approximation by ReLU shallow neural networks ⋮ SignReLU neural network and its approximation ability

Uses Software

• darch
• ImageNet
• AlexNet

Cites Work

• Unnamed Item
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• New Error Bounds for Deep ReLU Networks Using Sparse Grids
• Deep neural networks for rotation-invariance approximation and learning
• Nonparametric Regression Based on Hierarchical Interaction Models
• Sparse grids
• A Fast Learning Algorithm for Deep Belief Nets
• Theory of deep convolutional neural networks. III: Approximating radial functions

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