Practical recommendations for gradient-based training of deep architectures

@inproceedings{Bengio2012PracticalRF,
  title={Practical recommendations for gradient-based training of deep architectures},
  author={Yoshua Bengio},
  booktitle={Neural Networks: Tricks of the Trade},
  year={2012}
}
Learning algorithms related to artificial neural networks and in particular for Deep Learning may seem to involve many bells and whistles, called hyperparameters. This chapter is meant as a practical guide with recommendations for some of the most commonly used hyper-parameters, in particular in the context of learning algorithms based on backpropagated gradient and gradient-based optimization. It also discusses how to deal with the fact that more interesting results can be obtained when… CONTINUE READING

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