67 citations · 103 across the 18 of their papers we have counts for
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cs.LG2019★ 67 cited
Understanding Top-k Sparsification in Distributed Deep Learning
Shaohuai Shi, Xiaowen Chu, Ka Chun Cheung +1
Distributed stochastic gradient descent (SGD) algorithms are widely deployed in training large-scale deep learning models, while the communication overhead among workers becomes th…
cs.LG2018★ 6 cited
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
Jason Kuen, Xiangfei Kong, Zhe Lin +4
It is desirable to train convolutional networks (CNNs) to run more efficiently during inference. In many cases however, the computational budget that the system has for inference c…