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.
The objective is to sample a personalized trajectory ¯Xthat resides within this conditional manifold ¯M
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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.