  For a finite function class we describe the large sample limit of the
sequential Rademacher complexity in terms of the viscosity solution of a
$G$-heat equation. In the language of Peng's sublinear expectation theory, the
same quantity equals to the expected value of the largest order statistics of a
multidimensional $G$-normal random variable. We illustrate this result by
deriving upper and lower bounds for the asymptotic sequential Rademacher
complexity.
