no code implementations • 18 Aug 2021 • Simon Eberle, Arnulf Jentzen, Adrian Riekert, Georg S. Weiss
In the second main result of this article we prove in the training of such ANNs under the assumption that the target function and the density function of the probability distribution of the input data are piecewise polynomial that every non-divergent GF trajectory converges with an appropriate rate of convergence to a critical point and that the risk of the non-divergent GF trajectory converges with rate 1 to the risk of the critical point.
