The goal of this thesis is to develop practical algorithms with sound theoretical properties for three different subfields of nonlinear optimization: (i) Optimization Algorithms for Supervised Machine Learning; (ii) Derivative-Free Optimization; and (iii) Distributed Optimization. As such, the thesis is divided into three main chapters.
The focus of Chapter 2...