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Updated: Jan 29, 2026

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在不断变化的分配转移下,联合学习

Xuwei Tan1, Tian Xie1, Xue Zheng2

  • 1Department of Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.

Entropy (Basel, Switzerland)
|January 28, 2026
PubMed
概括

联合学习 (FL) 模型现在可以适应随时间变化的客户端数据分布. 新的算法,FedEvolve和FedEvp,确保模型对未来的数据进行概括,尽管模式在不断变化.

关键词:
ML 强度的强度 强度的强度分布式学习是一种分布式的学习.分销班的时间变化.联合学习的联合学习.

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