Rethinking the value of network pruning


Tags: paper ml
State: None
Source: https://arxiv.org/abs/1810.05270
Code: None

Summary

States LTH's method of finding a winning ticket is not necessary

  • It's commonly believed in literature that you have to: train, then prune and then fine-tune
  • But this is not necessary for unstructured pruning
  • Instead, you can find a better set of hparams for the optimization method, e.g. for SGD

For unstructured pruning this does not scale to ImageNet. They do not know why. Only comparable perf for smaller datasets (and models?)