相关实验视频

Updated: Sep 11, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

681

FedNolowe:一种基于损失的规范化加权聚合策略,用于在异质环境中实现强大的联合学习

Duy-Dong Le1, Tuong-Nguyen Huynh1, Anh-Khoa Tran2

  • 1Industrial University of Ho Chi Minh City (IUH), Ho Chi Minh City, Vietnam.

PloS one
|August 14, 2025
PubMed
概括

联邦规范化基于损失的加权聚合 (FedNolowe) 通过使用规范化培训损失来加权客户贡献来提高联邦学习稳定性. 这种方法增强了模型的融合,并减少了计算复杂性,以在不同的数据设置中获得更好的性能.

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