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cs.LG2025
Owen Sampling Accelerates Contribution Estimation in Federated Learning
Hossein KhademSohi, Hadi Hemmati, Jiayu Zhou +1
Federated Learning (FL) aggregates information from multiple clients to train a shared global model without exposing raw data. Accurately estimating each client's contribution is e…
cs.LG2022★ 5 cited
MDA: Availability-Aware Federated Learning Client Selection
Amin Eslami Abyane, Steve Drew, Hadi Hemmati
Recently, a new distributed learning scheme called Federated Learning (FL) has been introduced. FL is designed so that server never collects user-owned data meaning it is great at…