3 papers
stat.ML2026
Approximation Error and Complexity Bounds for ReLU Networks on Low-Regular Function Spaces
Owen Davis, Gianluca Geraci, Mohammad Motamed
In this work, we consider the approximation of a large class of bounded functions, with minimal regularity assumptions, by ReLU neural networks. We show that the approximation erro…
cs.LG2025
Deep Learning without Global Optimization by Random Fourier Neural Networks
Owen Davis, Gianluca Geraci, Mohammad Motamed
We introduce a new training algorithm for deep neural networks that utilize random complex exponential activation functions. Our approach employs a Markov Chain Monte Carlo samplin…
cs.LG2024
Residual Multi-Fidelity Neural Network Computing
Owen Davis, Mohammad Motamed, Raul Tempone
In this work, we consider the general problem of constructing a neural network surrogate model using multi-fidelity information. Motivated by error-complexity estimates for ReLU ne…