32 citations · 78 across the 9 of their papers we have counts for
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cs.CV2019
Adaptive Loss-aware Quantization for Multi-bit Networks
Zhongnan Qu, Zimu Zhou, Yun Cheng +1
We investigate the compression of deep neural networks by quantizing their weights and activations into multiple binary bases, known as multi-bit networks (MBNs), which accelerate…
cs.LG2019
Pruning-Aware Merging for Efficient Multitask Inference
Xiaoxi He, Dawei Gao, Zimu Zhou +2
Many mobile applications demand selective execution of multiple correlated deep learning inference tasks on resource-constrained platforms. Given a set of deep neural networks, eac…