Corpus ID: 43922508

Pushing the bounds of dropout

  title={Pushing the bounds of dropout},
  author={G{\'a}bor Melis and Charles Blundell and Tom{\'a}s Kocisk{\'y} and K. Hermann and Chris Dyer and P. Blunsom},
  • Gábor Melis, Charles Blundell, +3 authors P. Blunsom
  • Published 2018
  • Computer Science, Mathematics
  • ArXiv
  • We show that dropout training is best understood as performing MAP estimation concurrently for a family of conditional models whose objectives are themselves lower bounded by the original dropout objective. This discovery allows us to pick any model from this family after training, which leads to a substantial improvement on regularisation-heavy language modelling. The family includes models that compute a power mean over the sampled dropout masks, and their less stochastic subvariants with… CONTINUE READING
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