28 citations · 30 across the 9 of their papers we have counts for
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cs.LG2024
Accelerating Energy-Efficient Federated Learning in Cell-Free Networks with Adaptive Quantization
Afsaneh Mahmoudi, Ming Xiao, Emil Björnson
Federated Learning (FL) enables clients to share learning parameters instead of local data, reducing communication overhead. Traditional wireless networks face latency challenges w…
cs.LG2023
Learner Referral for Cost-Effective Federated Learning Over Hierarchical IoT Networks
Yulan Gao, Ziqiang Ye, Yue Xiao +1
The paradigm of federated learning (FL) to address data privacy concerns by locally training parameters on resource-constrained clients in a distributed manner has garnered signifi…