Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks

  title={Reintroducing Straight-Through Estimators as Principled Methods for Stochastic Binary Networks},
  author={Viktor Yanush and Alexander Shekhovtsov and Dmitry Molchanov and Dmitry P. Vetrov},
  booktitle={German Conference on Pattern Recognition},
Training neural networks with binary weights and activations is a challenging problem due to the lack of gradients and difficulty of optimization over discrete weights. Many successful experimental results have been recently achieved using the empirical straight-through estimation approach. This approach has generated a variety of ad-hoc rules for propagating gradients through non-differentiable activations and updating discrete weights. We put such methods on a solid basis by obtaining them as… 

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