A priori estimates for classification problems using neural networks

09/28/2020

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by   Weinan E, et al.

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We consider binary and multi-class classification problems using hypothesis classes of neural networks. For a given hypothesis class, we use Rademacher complexity estimates and direct approximation theorems to obtain a priori error estimates for regularized loss functionals.