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cs.CV2020
Precision Gating: Improving Neural Network Efficiency with Dynamic Dual-Precision Activations
Yichi Zhang, Ritchie Zhao, Weizhe Hua +3
We propose precision gating (PG), an end-to-end trainable dynamic dual-precision quantization technique for deep neural networks. PG computes most features in a low precision and o…
cs.CV2017★ 4 cited
Binarized Convolutional Neural Networks with Separable Filters for Efficient Hardware Acceleration
Jeng-Hau Lin, Tianwei Xing, Ritchie Zhao +4
State-of-the-art convolutional neural networks are enormously costly in both compute and memory, demanding massively parallel GPUs for execution. Such networks strain the computati…