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salvi

Andrey de Aguiar Salvi

Part 1

Pruning Neural Networks with Lottery Tickets in a MDP Approach

Suggestions for further work (possibly outside the scope of this course):

  • Do you plan to compare the performance of a pruned network with training a similarly structured network from scratch?
  • Use some kind of generalization for the policy (e.g. linear, NN, etc)

Stylistic comments:

  • Avoid passive voice
  • Keep the abstract to the point, focusing on the 4 key aspects I suggest here
  • Additionally, moreover, furthermore are often (but not always) an indication of poor structure, get rid of them (e.g. Moreover, MDPs are automatic planning algorithms, which means that we are trying to find a policy that is a universal problem solver). If you have multiple points to make, enumerate them and tell the reader at the outset what you want.

Part 2

Questions:

  • Why did you train the LeNet first?
  • Why not include actions to re-add features to the mask?