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Concentration bounds for two time scale stochastic approximation (1806.10798v1)
Published 28 Jun 2018 in math.OC
Abstract: 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.