Kolmogorov n-width theory plus PRESS statistics yield closed-form optimal spline resolution; KORE estimates bias/noise scales from two pilots and matches CV performance with far fewer fits.
n-Widths in Approximation Theory
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An accelerated alternating minimization algorithm is developed for low-rank matrix approximation in the Chebyshev norm, along with a proof that its limit points satisfy a new necessary optimality condition called 2-way alternance of rank r.
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Solve for the Hyperparameter, Skip the Search: Kolmogorov-Optimal Scaling Laws for Spline Regression
Kolmogorov n-width theory plus PRESS statistics yield closed-form optimal spline resolution; KORE estimates bias/noise scales from two pilots and matches CV performance with far fewer fits.
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Accelerated alternating minimization algorithm for low-rank approximations in the Chebyshev norm
An accelerated alternating minimization algorithm is developed for low-rank matrix approximation in the Chebyshev norm, along with a proof that its limit points satisfy a new necessary optimality condition called 2-way alternance of rank r.