New paper: principal component regression beats every monotone spectral filter, incl. ridge and GD
kfountou · x · 2026-10-01
In a new paper, junokim and coauthors show that principal component regression (PCR) matches, up to constants, the best possible monotone spectral filter on every problem instance — including gradient descent and ridge regression — reframing what 'optimal' means for solving linear regression.
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