Choong Seon Hong / Latif U. Khan / Zhu Han / Dawei Chen / Walid Saad / Mingzhe Chen
Federated Learning for Wireless Networks
- Springer Nature Singapore
- 2021
- Gebunden
- 268 Seiten
- ISBN 9789811649622
Recently machine learning schemes have attained significant attention as key enablers for next-generation wireless systems. Currently, wireless systems are mostly using machine learning schemes that are based on centralizing the training and inference processes by migrating the end-devices data to a third party centralized location. However, these schemes lead to end-devices privacy leakage. To address these issues, one can use a distributed machine learning at network edge. In this context, federated learning (FL) is one of most important distributed learning algorithm, allowing devices to train a shared machine learning model while keeping data locally. However, applying FL in wireless networks and optimizing the performance involves a
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