Nonparametric regression with modified ReLU networks

DOI10.1016/j.spl.2022.109624OpenAlexW4286512109MaRDI QIDQ2081757

Hailin Sang, Aleksandr Beknazaryan

Publication date: 30 September 2022

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2207.08306

zbMATH Keywords

neural networksnonparametric regression\( l_p\) regularizationsconvex penalties

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• reccv

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Introductory lectures on convex optimization. A basic course.
• Function approximation by deep neural networks with parameters \(\{0, \pm \frac{1}{2}, \pm 1,2\}\)
• Nonparametric regression using deep neural networks with ReLU activation function
• Optimal nonparametric inference via deep neural network
• The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network
• 10.1162/153244302760200713
• Sparse Approximate Solutions to Linear Systems
• Neural Network Learning
• Statistical guarantees for regularized neural networks