most citedAQUILA: Communication Efficient Federated Learning with Adaptive Quantization in Device Selection Strategy

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cs.LG2023

Federated PAC-Bayesian Learning on Non-IID data

Zihao Zhao, Yang Liu, Wenbo Ding +1

Existing research has either adapted the Probably Approximately Correct (PAC) Bayesian framework for federated learning (FL) or used information-theoretic PAC-Bayesian bounds while…

cs.LG2023★ 1 cited

AQUILA: Communication Efficient Federated Learning with Adaptive Quantization in Device Selection Strategy

Zihao Zhao, Yuzhu Mao, Zhenpeng Shi +4

The widespread adoption of Federated Learning (FL), a privacy-preserving distributed learning methodology, has been impeded by the challenge of high communication overheads, typica…