A description of perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees. In nearly al

A presentation of general results for discussing local optimality and computation of the expansion of value function and approximate solution of optimization pr

Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programm

Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programm

This book presents theoretical results, including an extension of constant rank and implicit function theorems, continuity and stability bounds results for infi