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cs.LG2021
FedH2L: Federated Learning with Model and Statistical Heterogeneity
Yiying Li, Wei Zhou, Huaimin Wang +2
Federated learning (FL) enables distributed participants to collectively learn a strong global model without sacrificing their individual data privacy. Mainstream FL approaches req…
cs.LG2018
Collaborative Deep Learning Across Multiple Data Centers
Kele Xu, Haibo Mi, Dawei Feng +4
Valuable training data is often owned by independent organizations and located in multiple data centers. Most deep learning approaches require to centralize the multi-datacenter da…