For ridgeless least squares with a spiked covariance, the asymptotic prediction risk is a closed-form function of spike eigenvalues, the aspect ratio, and target-spike alignment.
Consistency of AIC and BIC in estimating the number of significant components in high-dimensional principal component analysis
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High-dimensional ridgeless least squares interpolation under spiked covariance structures
For ridgeless least squares with a spiked covariance, the asymptotic prediction risk is a closed-form function of spike eigenvalues, the aspect ratio, and target-spike alignment.