Unintuitive Properties of Deep Neural Networks - Slides to talk by Hugo Larochelle


Slides to a talk given by Hugo Larochelle at the 2017 Deep Learning School in Montreal the video of which is unfortunately not yet available. The talk list a number of unintuitive properties of deep neural networks which we do not yet fully understand and contains links to the papers exploring these points:

  • They can make dumb errors
  • They are strangely non-convex
  • They work best when badly trained
  • They can easily memorize
  • They can be compressed
  • They are influenced by initialization and first examples, yet they forget what they learned.


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