19 citations · 88 across the 27 of their papers we have counts for
Showing 2018 · cs.LGShow all
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cs.LG2018★ 4 cited
AXNet: ApproXimate computing using an end-to-end trainable neural network
Zhenghao Peng, Xuyang Chen, Chengwen Xu +4
Neural network based approximate computing is a universal architecture promising to gain tremendous energy-efficiency for many error resilient applications. To guarantee the approx…
cs.LG2018
Approximate Random Dropout
Zhuoran Song, Ru Wang, Dongyu Ru +5
The training phases of Deep neural network~(DNN) consumes enormous processing time and energy. Compression techniques utilizing the sparsity of DNNs can effectively accelerate the…