WNQ uses weight normalization to reshape weight distributions and reduce quantization error, outperforming baselines on CIFAR-100 and ImageNet.
Binaryconnect: Training deep neural networks with binary weights during propagations
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Weight Normalization based Quantization for Deep Neural Network Compression
WNQ uses weight normalization to reshape weight distributions and reduce quantization error, outperforming baselines on CIFAR-100 and ImageNet.