SMASH: One-Shot Model Architecture Search through HyperNetworks

@article{Brock2017SMASHOM,
  title={SMASH: One-Shot Model Architecture Search through HyperNetworks},
  author={Andrew Brock and Theodore Lim and James M. Ritchie and Nick Weston},
  journal={CoRR},
  year={2017},
  volume={abs/1708.05344}
}
Designing architectures for deep neural networks requires expert knowledge and substantial computation time. We propose a technique to accelerate architecture selection by learning an auxiliary HyperNet that generates the weights of a main model conditioned on that model’s architecture. By comparing the relative validation performance of networks with HyperNet-generated weights, we can effectively search over a wide range of architectures at the cost of a single training run. To facilitate this… CONTINUE READING
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