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Updated: Jul 20, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Published on: December 6, 2024

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通过局部适应性修改优化器进行高效的联合学习,具有线性加速度.

Yan Sun, Li Shen, Hao Sun

    IEEE transactions on pattern analysis and machine intelligence
    |August 1, 2023
    PubMed
    概括

    联邦局部ADaptive修改优化器 (FedLADA) 通过使用动量来纠正局部模型漂移并提高训练速度来增强联合学习. 这种新的方法实现了更高的准确性,并减少了分布式机器学习中的通信回合.

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