A Global Universality of Two-Layer Neural Networks with ReLU Activations
Naoya Hatano, Masahiro Ikeda, Isao Ishikawa, Yoshihiro Sawano · Journal of Function Spaces · 2021
In the present study, we investigate a universality of neural networks, which concerns a density of the set of two-layer neural networks in function spaces. There are many works that handle the convergence over compact sets. In the present paper, we consider a global convergence by introducing a norm suitably, so that our results will be uniform over any compact set.