Analysis of the expected $L_2$ error of an over-parametrized deep neural network estimate learned by gradient descent without regularization

Selina Drews, Michael Kohler

Recent results show that estimates defined by over-parametrized deep neural networks learned by applying gradient descent to a regularized empirical $L_2$ risk are universally cons…