@inproceedings{maas2013rectifier,
  title={Rectifier nonlinearities improve neural network acoustic models},
  author={Maas, Andrew L and Hannun, Awni Y and Ng, Andrew Y},
  booktitle={Proc. ICML},
  volume={30},
  number={1},
  year={2013}
}

@inproceedings{nair2010rectified,
  title={Rectified linear units improve restricted {Boltzmann} machines},
  author={Nair, Vinod and Hinton, Geoffrey E},
  booktitle={Proc ICML},
  pages={807--814},
  year={2010}
}

@article{clevert2015fast,
  title={Fast and accurate deep network learning by exponential linear units ({ELU}s)},
  author={Clevert, Djork-Arn{\'e} and Unterthiner, Thomas and Hochreiter, Sepp},
  journal={arXiv preprint arXiv:1511.07289},
  year={2015}
}
@article{klambauer2017self,
  title={Self-Normalizing Neural Networks},
  author={Klambauer, G{\"u}nter and Unterthiner, Thomas and Mayr, Andreas and Hochreiter, Sepp},
  journal={arXiv preprint arXiv:1706.02515},
  year={2017}
}

@article{cohen2017emnist,
  title = {{EMNIST}: an extension of {MNIST} to handwritten letters},
  author = {Cohen, G. and Afshar, S. and Tapson, J. and van Schaik, A.},
  journal={arXiv preprint arXiv:1702.05373},
  year={2017},
  url = {https://arxiv.org/abs/1702.05373}
}

@inproceedings{kingma2015adam,
  title = {Adam: A Method for Stochastic Optimization},
  author = {Diederik P. Kingma and Jimmy Ba},
  booktitle = {ICML},
  year = {2015},
  url = {https://arxiv.org/abs/1412.6980}
}

@article{tieleman2012rmsprop,
  title={Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude},
  author={Tieleman, T. and Hinton, G. E.},
  journal={COURSERA: Neural Networks for Machine Learning},
  volume={4},
  number={2},
  year={2012},
  url = {https://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf}
}

@inproceedings{ioffe2015batch,
  title={Batch normalization: Accelerating deep network training by reducing internal covariate shift},
  author={Ioffe, Sergey and Szegedy, Christian},
  booktitle={ICML},
  pages={448--456},
  year={2015},
  url = {http://proceedings.mlr.press/v37/ioffe15.html}
}