Corpus ID: 220793772

FedML: A Research Library and Benchmark for Federated Machine Learning

@article{He2020FedMLAR,
  title={FedML: A Research Library and Benchmark for Federated Machine Learning},
  author={Chaoyang He and Songze Li and Jinhyun So and Mi Zhang and Hongyi Wang and Xiaoyang Wang and Praneeth Vepakomma and Abhishek Singh and Han Qiu and Li Shen and P. Zhao and Yan Kang and Yang Liu and R. Raskar and Qiang Yang and M. Annavaram and S. Avestimehr},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.13518}
}
Federated learning is a rapidly growing research field in the machine learning domain. Although considerable research efforts have been made, existing libraries cannot adequately support diverse algorithmic development (e.g., diverse topology and flexible message exchange), and inconsistent dataset and model usage in experiments make fair comparisons difficult. In this work, we introduce FedML, an open research library and benchmark that facilitates the development of new federated learning… Expand
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