Optimal approximation of continuous functions by very deep ReLU networks

10 Feb 2018Dmitry Yarotsky

We consider approximations of general continuous functions on finite-dimensional cubes by general deep ReLU neural networks and study the approximation rates with respect to the modulus of continuity of the function and the total number of weights $W$ in the network. We establish the complete phase diagram of feasible approximation rates and show that it includes two distinct phases... (read more)

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