Fixed-point optimization of deep neural networks with adaptive step size retraining

@article{Shin2017FixedpointOO,
  title={Fixed-point optimization of deep neural networks with adaptive step size retraining},
  author={Sungho Shin and Yoonho Boo and Wonyong Sung},
  journal={2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2017},
  pages={1203-1207}
}
Fixed-point optimization of deep neural networks plays an important role in hardware based design and low-power implementations. Many deep neural networks show fairly good performance even with 2- or 3-bit precision when quantized weights are fine-tuned by retraining. We propose an improved fixed-point optimization algorithm that estimates the quantization step size dynamically during the retraining. In addition, a gradual quantization scheme is also tested, which sequentially applies fixed… CONTINUE READING
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