Personalisation of Federated Learning Models Through Knowledge Distillation on Decentralised Data-Reference-Cited by-同舟云学术

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Personalisation of Federated Learning Models Through Knowledge Distillation on Decentralised Data

Published:2023-12-04 Issue: Volume:139 Page:56-61
ISSN:
Container-title:2023 IEEE Globecom Workshops (GC Wkshps)
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Author:

SiniosoGlou Ilias¹,Xouveroudis Konstantinos²,Argyriou Vasileios³,Lagkas Thomas⁴,Saoulidis Theocharis⁵,Fragulis George¹,Goudos Sotirios K.⁶,Sarigiannidis Panagiotis¹

Affiliation:

1. University of Western Macedonia,Department of Electrical and Computer Engineering,Greece

2. MetaMind Innovations P.C.,R&D Department,Greece

3. Kingston University,Department of Networks and Digital Media,United Kingdom

4. International Hellenic University,Department of Computer Science,Greece

5. Sidroco Holdings Ltd,Nicosia,Cyprus

6. Aristotle University of Thessaloniki,Physics Department,Thessaloniki,Greece

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10464388/10464393/10464710.pdf?arnumber=10464710

Reference20 articles.

1. Unsupervised Ethical Equity Evaluation of Adversarial Federated Networks

2. Communication-Efficient Learning of Deep Networks from Decentralized Data;McMahan

3. Data-free knowledge distillation for heterogeneous federated learning;Zhu

4. Long Short-Term Memory

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