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Perfectly rank-matched tensor factorizations still suffer from quartically flat optimization valleys whenever the underlying Fourier slice ranks are nonuniform.
R-ItCUR achieves accurate tensor recovery even in the presence of significant outliers, showcasing its robustness and efficiency in real-world applications.
