42 citations · 182 across the 23 of their papers we have counts for
Showing 2021Show all
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cs.DC2021★ 1 cited
Communication-Efficient Distributed Learning via Sparse and Adaptive Stochastic Gradient
Xiaoge Deng, Dongsheng Li, Tao Sun +1
Gradient-based optimization methods implemented on distributed computing architectures are increasingly used to tackle large-scale machine learning applications. A key bottleneck i…
cs.DC2021★ 23 cited
Decentralized Federated Averaging
Tao Sun, Dongsheng Li, Bao Wang
Federated averaging (FedAvg) is a communication efficient algorithm for the distributed training with an enormous number of clients. In FedAvg, clients keep their data locally for…
cs.LG2021
Inertial Proximal Deep Learning Alternating Minimization for Efficient Neutral Network Training
Linbo Qiao, Tao Sun, Hengyue Pan +1
In recent years, the Deep Learning Alternating Minimization (DLAM), which is actually the alternating minimization applied to the penalty form of the deep neutral networks training…