A regularizer claimed to minimize a VC dimension bound for neural networks is proposed, but the bound derivation drops a required term and the empirical gains over L2 regularization are inconsistent.
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Smaller Models, Better Generalization
A regularizer claimed to minimize a VC dimension bound for neural networks is proposed, but the bound derivation drops a required term and the empirical gains over L2 regularization are inconsistent.