HMQ: Hardware Friendly Mixed Precision Quantization Block for CNNs

Author:

Habi Hai Victor,Jennings Roy H.,Netzer Arnon

Publisher

Springer International Publishing

Reference49 articles.

1. Banner, R., Nahshan, Y., Soudry, D.: Post training 4-bit quantization of convolutional networks for rapid-deployment. In: Advances in Neural Information Processing Systems, pp. 7948–7956 (2019)

2. Baskin, C., et al.: Nice: noise injection and clamping estimation for neural network quantization. arXiv preprint arXiv:1810.00162 (2018)

3. Baskin, C., et al.: Uniq: uniform noise injection for non-uniform quantization of neural networks. arXiv preprint arXiv:1804.10969 (2018)

4. Bengio, Y., Léonard, N., Courville, A.: Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv preprint arXiv:1308.3432 (2013)

5. Cai, Y., et al.: Zeroq: a novel zero shot quantization framework. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 13169–13178 (2020)

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