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Model compression and hardware acceleration for neural networks: A comprehensive survey
L Deng, G Li, S Han, L Shi, Y ** and magnitude-aware differentiation for improved quantization-aware training
Data clip** is crucial in reducing noise in quantization operations and improving the
achievable accuracy of quantization-aware training (QAT). Current practices rely on …
achievable accuracy of quantization-aware training (QAT). Current practices rely on …
Deep k-means: Re-training and parameter sharing with harder cluster assignments for compressing deep convolutions
The current trend of pushing CNNs deeper with convolutions has created a pressing
demand to achieve higher compression gains on CNNs where convolutions dominate the …
demand to achieve higher compression gains on CNNs where convolutions dominate the …