$\ell_{\infty}$ Vector Contraction for Rademacher Complexity

Rademacher complexity plays a fundamental role in learning theory, where it tightly bounds the supremum of the empirical process ( Koltchinskii and Panchenko, 2000; Bartlett and Mendelson, 2003) and is used to prove generalization guarantees for empiric al risk minimization and other learning rules.