Shallow neural network approximation in mixed Sobolev spaces
We investigate the best $L_2$ approximation of mixed Sobolev spaces by shallow neural networks with $n$ neurons and general activation functions. We first establish an activation-independent Fourier-block principle: if an activation has univariate approximation order $\rho$ in the sense of the Fourier-block property, t...
Yuwen Li, Guozhi Zhang
· 0 citations