In this thesis, we aim to develop efficient algorithms with theoretical guarantees for noisy nonlinear optimization problems, with and without constraints, under various different assumptions. Apart from Chapter 1 which provides relevant backgrounds, the remaining of thesis is divided into four chapters. In Chapter 2, we establish the theoretical convergence...
The goal of this thesis is to design practical algorithms for nonlinear optimization in the case when the objective function is stochastic or nonsmooth. The thesis is divided into three chapters. Chapter 1 describes an active-set method for the minimization of an objective function that is structurally nonsmooth, viz., it...