Federated Learning for Wireless Networks
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…
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Produktdetails
Weitere Autoren: Khan, Latif U. / Chen, Mingzhe
- ISBN: 978-981-1649-62-2
- EAN: 9789811649622
- Produktnummer: 36907253
- Verlag: Springer Nature
- Sprache: Englisch
- Erscheinungsjahr: 2021
- Seitenangabe: 268 S.
- Masse: H24.1 cm x B16.0 cm x D2.0 cm 571 g
- Auflage: 2021
- Gewicht: 571
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