Antonio Falcó

Resolution-Consistent Greedy Neural Approximation on Infinite-Dimensional Spaces

We develop constructive approximation and learning guarantees for shallow neural models with infinite-dimensional inputs observed through finitely many coordinates. The analysis is based on a parameter-normalized neural dictionary and its associated weighted variation class. Within this class, the approximation error s...