Search Results for author: Youngtak Sohn

Found 2 papers, 0 papers with code

Universality of max-margin classifiers

no code implementations29 Sep 2023 Andrea Montanari, Feng Ruan, Basil Saeed, Youngtak Sohn

Working in the high-dimensional regime in which the number of features $p$, the number of samples $n$ and the input dimension $d$ (in the nonlinear featurization setting) diverge, with ratios of order one, we prove a universality result establishing that the asymptotic behavior is completely determined by the expected covariance of feature vectors and by the covariance between features and labels.

Binary Classification

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