Review of “New error bounds for deep ReLU networks using sparse grids”
Course project, University of Edinburgh, School of Mathematics, 2021-03
This is a paper aims to address the problem, why and when deep networks can lessen or break the curse of dimensionality. Instead of focusing on a particular set of functions which have a very special structure, they consider functions in the Korobov spaces which is more general for high dimensional multivariate approximation.