10 citations · 18 across the 6 of their papers we have counts for
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cs.DC2021
From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization
Feijie Wu, Song Guo, Haozhao Wang +4
In the setting of federated optimization, where a global model is aggregated periodically, step asynchronism occurs when participants conduct model training by efficiently utilizin…
cs.DC2019★ 10 cited
Gradient Scheduling with Global Momentum for Non-IID Data Distributed Asynchronous Training
Chengjie Li, Ruixuan Li, Haozhao Wang +4
Distributed asynchronous offline training has received widespread attention in recent years because of its high performance on large-scale data and complex models. As data are dist…
cs.DC2019★ 3 cited
Heterogeneity-aware Gradient Coding for Straggler Tolerance
Haozhao Wang, Song Guo, Bin Tang +2
Gradient descent algorithms are widely used in machine learning. In order to deal with huge volume of data, we consider the implementation of gradient descent algorithms in a distr…