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New DRiC method improves online residual correction for forecasters

Researchers have developed DRiC (DCT Ridge Corrector), a novel method for online residual correction of frozen multivariate forecasters, particularly effective under label delay conditions. DRiC aims to minimize retained state while maximizing error reduction by fitting ridge regressions to the leading discrete cosine transform (DCT) coefficients. Its variants, DRiC-L and DRiC-G, offer different approaches to channel pooling, with DRiC-G demonstrating strong performance on high-channel datasets like Electricity and Traffic, despite some comparators being more accurate with significantly more state. AI

IMPACT Introduces a novel technique for improving forecasting accuracy with reduced state retention, potentially benefiting time-series analysis in various domains.

RANK_REASON The cluster contains a research paper detailing a new method for multivariate forecasters. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

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New DRiC method improves online residual correction for forecasters

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The cluster contains a research paper detailing a new method for multivariate forecasters. [lever_c_demoted from research: ic=1 ai=1.0]
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  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…