  Viewing a two time scale stochastic approximation scheme as a noisy
discretization of a singularly perturbed differential equation, we obtain a
concentration bound for its iterates that captures its behavior with
quantifiable high probability. This uses Alekseev's nonlinear variation of
constants formula and a martingale concentration inequality and extends the
corresponding results for single time scale stochastic approximation.
