… Communication efficiency optimization of federated learning for computing and network …
@article{title="Communication efficiency optimization of federated learning for computing …

… Federated Learning (FL) is an innovative technology that effectively addresses these
challenges by leveraging the characteristics of distributed learning. It elevates the performance of …

… such as smart grid, wireless communications, and data science. … different applications in
communications and signal processing. … and unsupervised federated learning are considered. A …

… wireless networks through federated learning [C]椅2020 IEEE 21st International Symposium
on A World of Wireless, … Communication鄄efficient federated learning for wireless edge …

… Efficient wireless federated learning algorithm based on 1‑bit … In the wireless Federated
Learning (FL) architecture, the … model, thus causing a large communication overhead and power …

… training framework, federated learning has broad applications in wireless … federated average
algorithm, we attempt to explain why the impact of non-IID datasets on federated learning …

… Therefore, a distributed wireless traffic prediction … and communication overhead. Based
on the distributed architecture, a wireless traffic prediction model based on federated learning …

… However, the wireless bandwidth is limited, and the … using federated learning for training
deep neural networks. The simulation results show that the proposed federated deep learning-…

… federated learning and machine learning approaches to improve inventory management.
Federated learning is … traffic on a low-bandwidth wireless network and power consumption. The …

… -based federated intrusion detection algorithm for wireless sensor … Federated learning for
internet of things: Recent advances, taxonomy, and open challenges[J]. IEEE Communications …