CORAL learns block-diagonal kernel self-representation matrices per time window to identify, track, and forecast concept drift in co-evolving time series, with modest reported RMSE gains over baselines.
Box and jenkins: time series analysis, forecasting and control
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CORAL: Concept Drift Representation Learning for Co-evolving Time-series
CORAL learns block-diagonal kernel self-representation matrices per time window to identify, track, and forecast concept drift in co-evolving time series, with modest reported RMSE gains over baselines.