Rate distortion optimization for adaptive gradient quantization in federated learning

NQFL: Nonuniform Quantization for Communication Efficient Federated Learning

G Chen, K Xie, Y Tu, T Song, Y Xu… - IEEE Communications …, 2023 - ieeexplore.ieee.org
Federated learning (FL), as a potential machine learning framework for privacy preservation,
has gained significant attention. However, the considerable communication overhead …
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Energy-Efficient Wireless Federated Learning via Doubly Adaptive Quantization

X Han, W Chen, J Li, M Ding, Q Wu, K Wei… - arXiv preprint arXiv …, 2024 - arxiv.org
Federated learning (FL) has been recognized as a viable distributed learning paradigm for
training a machine learning model across distributed clients without uploading raw data …
被引用次数：1 相关文章 所有 2 个版本

Federated Learning with Kalman Filter for Intrusion Detection in IoT Environment

Z Almesleh, A Gouissem… - 2024 IEEE 8th Energy …, 2024 - ieeexplore.ieee.org
Enhancing the IoT (Internet of Things) network for reliability prompted a heightened focus on
device security, given their diverse characteristics and sensitive data exchange. Federated …
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