… FederatedLearning (FL) is an innovative technology that effectively addresses these challenges by leveraging the characteristics of distributed learning. It elevates the performance of …
M Servetnyk - 交通大學電機資訊國際學位學程學位論文, 2020 - airitilibrary.com
… such as smart grid, wirelesscommunications, and data science. … different applications in communications and signal processing. … and unsupervised federatedlearning are considered. A …
… wireless networks through federatedlearning [C]椅2020 IEEE 21st International Symposium on A World of Wireless, … Communication鄄efficient federatedlearning for wireless edge …
… Efficient wirelessfederatedlearning algorithm based on 1‑bit … In the wirelessFederated Learning (FL) architecture, the … model, thus causing a large communication overhead and power …
… training framework, federatedlearning has broad applications in wireless … federated average algorithm, we attempt to explain why the impact of non-IID datasets on federatedlearning …
… Therefore, a distributed wireless traffic prediction … and communication overhead. Based on the distributed architecture, a wireless traffic prediction model based on federatedlearning …
… However, the wireless bandwidth is limited, and the … using federatedlearning for training deep neural networks. The simulation results show that the proposed federated deep learning-…
… federatedlearning and machine learning approaches to improve inventory management. Federatedlearning is … traffic on a low-bandwidth wireless network and power consumption. The …
… -based federated intrusion detection algorithm for wireless sensor … Federatedlearning for internet of things: Recent advances, taxonomy, and open challenges[J]. IEEE Communications …