50 citations · 213 across the 25 of their papers we have counts for
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cs.DC2021★ 1 cited
S2 Reducer: High-Performance Sparse Communication to Accelerate Distributed Deep Learning
Keshi Ge, Yongquan Fu, Zhiquan Lai +2
Distributed stochastic gradient descent (SGD) approach has been widely used in large-scale deep learning, and the gradient collective method is vital to ensure the training scalabi…
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…