BranchyNet: Fast inference via early exiting from deep neural networks

@article{Teerapittayanon2016BranchyNetFI,
  title={BranchyNet: Fast inference via early exiting from deep neural networks},
  author={Surat Teerapittayanon and Bradley McDanel and H. T. Kung},
  journal={2016 23rd International Conference on Pattern Recognition (ICPR)},
  year={2016},
  pages={2464-2469}
}
Deep neural networks are state of the art methods for many learning tasks due to their ability to extract increasingly better features at each network layer. However, the improved performance of additional layers in a deep network comes at the cost of added latency and energy usage in feedforward inference. As networks continue to get deeper and larger, these costs become more prohibitive for real-time and energy-sensitive applications. To address this issue, we present BranchyNet, a novel deep… CONTINUE READING
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