I'm looking for a good review paper or book chapter that offers an accessible introduction to the computational complexity of training neural networks for classification problems. Some time back, I found a text book that stated that training an MLP network is NP-Complete, and there is this paper - but I haven't found much beyond that.

In particular, I'm trying to study questions like:

  1. How is training complexity related to network topology ?
  2. How is training complexity related to the complexity of the decision boundary?

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