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English(EN) Local and Global Recursive Ridge Regression for Online Residual Correction of Frozen Multivariate Forecasters under Label Delay

新的DRiC方法改进了预测器的在线残差校正

研究人员开发了DRiC(DCT岭回归校正器),一种用于冻结多元预测器的在线残差校正的新颖方法,在标签延迟条件下尤其有效。DRiC通过将岭回归拟合到领先的离散余弦变换(DCT)系数,旨在最小化保留状态同时最大化误差减少。其变体DRiC-L和DRiC-G提供了不同的通道池化方法,尽管一些比较器在状态显著更多的情况下更准确,但DRiC-G在Electricity和Traffic等高通道数据集上表现强劲。 AI

影响 引入了一种新颖的技术,以减少状态保留来提高预测准确性,可能使时间序列分析在各个领域受益。

排序理由 该集群包含一篇详细介绍多元预测器新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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新的DRiC方法改进了预测器的在线残差校正

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该集群包含一篇详细介绍多元预测器新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Takumi Fujimoto, Hiroaki Nishi ·

    Local and Global Recursive Ridge Regression for Online Residual Correction of Frozen Multivariate Forecasters under Label Delay

    arXiv:2610.29604v1 Announce Type: new Abstract: A frozen multi-horizon forecaster can be corrected online from its own residuals. However, under label delay the target of a block arrives only after the whole horizon has passed, and the corrector's retained state grows with the nu…