Point-wise losses induce an irreducible bias in time series forecasting governed by sequence length and structural signal-to-noise ratio; DFT/DWT orthogonalization plus a harmonized lp norm reduces it and improves accuracy.
Here, the optimization target is the time series values themselves, which inherently possess strong temporal correlations and deterministic structures (e.g., trend and periodicity)
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The Procrustean Bed of Time Series: The Optimization Bias in Point-wise Loss Functions
Point-wise losses induce an irreducible bias in time series forecasting governed by sequence length and structural signal-to-noise ratio; DFT/DWT orthogonalization plus a harmonized lp norm reduces it and improves accuracy.