Intermittent Pulling with Local Compensation for Communication-Efficient Federated Learning

22 Jan 2020Haozhao WangZhihao QuSong GuoXin GaoRuixuan LiBaoliu Ye

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 Stochastic Gradient Descent (SGD) algorithm for large-scale Federated Learning is the communication overhead on pushing local gradients and pulling global model... (read more)

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