AI RESEARCH
Aergia: Leveraging Heterogeneity in Federated Learning Systems
arXiv CS.LG
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ArXi:2210.06154v2 Announce Type: replace Federated Learning (FL) is a popular approach for distributed deep learning that prevents the pooling of large amounts of data in a central server. FL relies on clients to update a global model using their local datasets. Classical FL algorithms use a central federator that, for each