I am new to the domain of Machine learning. I have been asked to present a paper related to the mathematics behind the depth separations in Neural Networks (by Itay Safran, Ronen Eldan and Ohad Shamir). I have been having a hard time in understanding the paper.

I am looking for easy papers to learn the foundation so that I can move on to this paper. Please drop the link to any papers that you think I should read first.

  • $\begingroup$ Please, attach a link to the paper you are talking about. $\endgroup$ – Vladislav Bezhentsev Nov 21 '20 at 21:54
  • $\begingroup$ Papers usually cite earlier work on similar topics. It should be in the introduction or in a section titled related work. $\endgroup$ – Yuval Filmus Nov 21 '20 at 22:58
  • $\begingroup$ @VladislavBezhentsev ... proceedings.mlr.press/v99/safran19a/safran19a.pdf $\endgroup$ – Mariam Nov 22 '20 at 0:22

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