1. A Deep Look into Logarithmic Quantization of Model Parameters in Neural Networks
2. Matthieu Courbariaux Yoshua Bengio and Jean-Pierre David. 2016. BinaryConnect: Training Deep Neural Networks with binary weights during propagations. arxiv:1511.00363 [cs.LG] Matthieu Courbariaux Yoshua Bengio and Jean-Pierre David. 2016. BinaryConnect: Training Deep Neural Networks with binary weights during propagations. arxiv:1511.00363 [cs.LG]
3. [
3
] CUDA Toolkit [n. d.]. https://developer.nvidia.com/cuda-toolkit/. [3] CUDA Toolkit [n. d.]. https://developer.nvidia.com/cuda-toolkit/.
4. Diederik P. Kingma and Jimmy Ba . 2017 . Adam : A Method for Stochastic Optimization . arxiv:1412.6980 [cs.LG] Diederik P. Kingma and Jimmy Ba. 2017. Adam: A Method for Stochastic Optimization. arxiv:1412.6980 [cs.LG]
5. Fengfu Li Bin Liu Xiaoxing Wang Bo Zhang and Junchi Yan. 2022. Ternary Weight Networks. arxiv:1605.04711 [cs.CV] Fengfu Li Bin Liu Xiaoxing Wang Bo Zhang and Junchi Yan. 2022. Ternary Weight Networks. arxiv:1605.04711 [cs.CV]