Login / Signup

Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses.

Charles G. FryeJames SimonNeha S. WadiaAndrew LigeraldeMichael Robert DeWeeseKristofer E. Bouchard
Published in: Neural Comput. (2021)
Keyphrases
  • significant improvement
  • multiscale
  • critical points
  • data sets
  • image processing
  • bayesian networks
  • pattern recognition
  • object recognition
  • computational cost
  • peer to peer
  • network model
  • gradient method
  • deep structure