Harro Walk

On the rate of convergence of a neural network regression estimate learned by gradient descent

2019 · arXiv (Cornell University)

Nonparametric regression with random design is considered. Estimates are defined by minimzing a penalized empirical $L_2$ risk over a suitably chosen class of neural networks with one hidden layer via gradient descent. Here, the gradient …