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Thanks, I'll look up the journals you suggest. By "just" I meant to clarify the use of "ML". It's often used to mean "deep learning" and while I thought you di

Thanks, I'll look up the journals you suggest. By "just" I meant to clarify the use of "ML". It's often used to mean "deep learning" and while I thought you didn't use it that way I wanted to make sure. I normally think of neural nets as a primarily connectionist approach to machine learning (although not necessarily statistical: the first artificial neuron was propositional logic-based). I'm curious to read research that treats them in a different manner. Can you recommend some? Thanks in advance (again)!

enriquto 5y ago
Look for example the article "Approximation Spaces of Deep Neural Networks" by Gribonval et al. It contains a nice review of the spaces of functions that are represented by neural networks. It's just about properties of neural networks and their computing power, depending on their depth, width, skip connections, and nonlinearity type. The weights are fixed constants, there's no training whatsoever.
- YeGoblynQueenne 5y ago
  Thanks!