FedLoop: A P2P Personalized Federated Learning Method on Heterogeneous Data
Author:
Affiliation:
1. Universiti Malaya,Faculty of Computer Science and Information Technology,Kuala Lumpur,Malaysia
2. HoHai University,Department of Telecommunication,Changzhou,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10371778/10371788/10371829.pdf?arnumber=10371829
Reference14 articles.
1. Communication-efficient learning of deep networks from decentralized data;McMahan;Artificial intelligence and statistics,2017
2. Towards Personalized Federated Learning
3. Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics;Ramasesh
4. No fear of heterogeneity: Classifier calibration for federated learning with non-iid data;Luo;Advances in Neural Information Processing Systems,2021
5. Advances and Open Problems in Federated Learning
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