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Quantization of Neural Networks

  • Baochang Zhang,
  • Tiancheng Wang,
  • Sheng Xu,
  • David Doermann

摘要

Quantization has emerged as a highly successful strategy for both training and inference of neural networks (NN). While the challenges of numerical representation and quantization have been long-standing in digital computing, NNs offer unique opportunities for advancements in this area. Although this survey primarily focuses on quantization for inference, it is important to acknowledge that quantization has also shown promise in NN training.