10 citations · 21 across the 7 of their papers we have counts for
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cs.LG2020★ 4 cited
Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning
Haozhao Wang, Zhihao Qu, Song Guo +3
Federated Learning is a powerful machine learning paradigm to cooperatively train a global model with highly distributed data. A major bottleneck on the performance of distributed…
cs.LG2019★ 1 cited
AccUDNN: A GPU Memory Efficient Accelerator for Training Ultra-deep Neural Networks
Jinrong Guo, Wantao Liu, Wang Wang +4
Typically, Ultra-deep neural network(UDNN) tends to yield high-quality model, but its training process is usually resource intensive and time-consuming. Modern GPU's scarce DRAM ca…