0.8LGJun 6, 2018
The effect of the choice of neural network depth and breadth on the size of its hypothesis spaceLech Szymanski, Brendan McCane, Michael Albert
We show that the number of unique function mappings in a neural network hypothesis space is inversely proportional to $\prod_lU_l!$, where $U_{l}$ is the number of neurons in the hidden layer $l$.