Revealing the Structure of Deep Neural Networks via Convex Duality

22 Feb 2020 Tolga Ergen Mert Pilanci

We study regularized deep neural networks (DNNs) and introduce a convex analytic framework to characterize the structure of the hidden layers. We show that a set of optimal hidden layer weights for a norm regularized DNN training problem can be explicitly found as the extreme points of a convex set... (read more)

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