Regularizing Activation Distribution for Training Binarized Deep Networks

CVPR 2019 Ruizhou DingTing-Wu ChinZeye LiuDiana Marculescu

Binarized Neural Networks (BNNs) can significantly reduce the inference latency and energy consumption in resource-constrained devices due to their pure-logical computation and fewer memory accesses. However, training BNNs is difficult since the activation flow encounters degeneration, saturation, and gradient mismatch problems... (read more)

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