From my reading of the first twenty or so pages, it appears to be a theory of how neural networks model images (the running example). The authors claim that popular neural network architectures can be reduced to particular cases of their model.
If this model can provide an explanation for the small noises impacting NN performance on images (from karpathy.github.io, posted to HN earlier today) then that would be rocking.
Nonetheless, it does not appear to be an experimental paper, rather providing a mathematical theory of some particular classification problems.
If this model can provide an explanation for the small noises impacting NN performance on images (from karpathy.github.io, posted to HN earlier today) then that would be rocking.
Nonetheless, it does not appear to be an experimental paper, rather providing a mathematical theory of some particular classification problems.