Effects of width-dependent model hyperparameters and ${\ell }_2$-regularization on the loss landscape of two-layer ReLU networks

Haruka Eshima, Makoto Yamada

Understanding deep neural networks remains a central challenge in machine learning. In particular, the theoretical properties of even two-layer ReLU networks, especially in the pre…