Dynamical stability and chaos in artificial neural network trajectories along training

HIGHLIGHTS

  • What: The aim of this work is to offer an illustration of this crossdisciplinary perspective. As the authors have mentioned already, in this work the authors investigate a quite simple learning task-a fully-connected, feed-forward neural_network with a single hidden layer trained for classification on the Iris dataset (Fisher, 1936). The authors can the values δij are iid realizations of a random variable δ. ^ define δ as the authors wish, but in this work the authors focus on the case where ^ δ^ ≡ U(-ϵ, ϵ). Exploring this question is one of the goals of this work.
  • Who: Andrea . . .

     

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