PSD Smoothness for Time Series

Background: Dataset Distillation (DD) aims to synthesize a small, compact dataset that can train a model as effectively as the original, large dataset.

Question / Future Work: Investigating the limitations of the theoretical justification provided for Harmonic Matching, specifically exploring whether the assumptions regarding the smoothness (Lipschitz continuity) of the Power Spectral Density (PSD) for general time series data are always met in real-world applications, and what impact violations of these assumptions have on the guaranteed bound for autocorrelation preservation.