3 papers
cs.LG2024
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…
stat.ML2024
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.LG2023
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…