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Weighted Data Selection: Sharp Upper-Half and Five-Dimensional Laws

arXiv:2610.00101v1 Announce Type: new Abstract: How much risk does a small reweighted training support retain? For finite weighted least squares with the minimum-norm learner, we prove the exact law $\Gamma_d(n)=3-n/d$ throughout $\lceil3d/2\rceil\leq n\leq2d-1$. The guarantee covers every observed…

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  1. 2026-10-02 04:00 · arXiv stat.ML
    Weighted Data Selection: Sharp Upper-Half and Five-Dimensional Laws

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