STOCHASTIC OPTIMIZATION: ALGORITHMS AND CONVERGENCE
Stochastic approximation is one of the oldest approaches for solving stochastic optimization problems. In the first part of the dissertation, we study the convergence and asymptotic normality of a generalized form of stochastic approximation algorithm with deterministic perturbation sequences. Both one-simulation and