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Showing results 1 to 4 of 4

Thesis
Communication-Efficient and Drift-Robust Federated Learning via Elastic Net
  • Seonhyeong Kim
  • 2023
  • Seonhyeong Kim. (2023). Communication-Efficient and Drift-Robust Federated Learning via Elastic Net. doi: 10.22677/THESIS.200000653511
  • DGIST
  • View : 245
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Article
Federated learning with knowledge distillation for multi-organ segmentation with partially labeled datasets
  • 2024-07
  • Kim, Soopil. (2024-07). Federated learning with knowledge distillation for multi-organ segmentation with partially labeled datasets. Medical Image Analysis, 95. doi: 10.1016/j.media.2024.103156
  • Elsevier
  • View : 80
  • Download : 0
Article
FedNN: Federated learning on concept drift data using weight and adaptive group normalizations
  • 2024-05
  • Kang, Myeongkyun. (2024-05). FedNN: Federated learning on concept drift data using weight and adaptive group normalizations. Pattern Recognition, 149. doi: 10.1016/j.patcog.2023.110230
  • Elsevier
  • View : 241
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Article
LightVeriFL: A Lightweight and Verifiable Secure Aggregation for Federated Learning
  • Buyukates, Baturalp ; 
  • So, Jinhyun ; 
  • Mahdavifar, Hessam ; 
  • Avestimehr, Salman
  • 2024-04
  • Buyukates, Baturalp. (2024-04). LightVeriFL: A Lightweight and Verifiable Secure Aggregation for Federated Learning. IEEE Journal on Selected Areas in Information Theory, 5, 285–301. doi: 10.1109/JSAIT.2024.3391849
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 264
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