11 citations · 38 across the 9 of their papers we have counts for
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cs.CV2018
Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks
Mengdi Wang, Qing Zhang, Jun Yang +2
In this work, we propose a graph-adaptive pruning (GAP) method for efficient inference of convolutional neural networks (CNNs). In this method, the network is viewed as a computati…
cs.DC2018
FusionStitching: Deep Fusion and Code Generation for Tensorflow Computations on GPUs
Guoping Long, Jun Yang, Kai Zhu +1
In recent years, there is a surge on machine learning applications in industry. Many of them are based on popular AI frameworks like Tensorflow, Torch, Caffe, or MxNet, etc, and ar…