关于流媒体噪音数据与分布转移的理论观点

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Updated: Jan 8, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
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Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

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Wenshui Luo, Shuo Chen, Tao Zhou

    IEEE transactions on pattern analysis and machine intelligence
    |December 11, 2025
    PubMed
    概括

    智能系统在不断学习中扎,原因是数据噪音和分布转移. 一个新的框架,CNLDD (Continual Noisy Label Learning on Drifting Data Streams),有效地减轻了灾难性遗忘,并改善了不断变化的数据集的性能.

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