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Updated: Jul 22, 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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卡尔达:改善多源时间序列域调整与对比的对抗性学习.

Garrett Wilson, Janardhan Rao Doppa, Diane J Cook

    IEEE transactions on pattern analysis and machine intelligence
    |July 24, 2023
    PubMed
    概括

    本研究介绍了CALDA,这是一种用于无监督域调整时间序列数据的新框架. 卡尔达通过利用跨源标签信息和弱监督来改善机器学习,优于现有方法.

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