Genericity in linear algebra and analysis with applications to optimization

This report gives a concise overview into genericity results for sets of matrices, linear and nonlinear equations as well as for unconstrained and constrained optimization problems. We present the generic behavior of non-parametric problems and parametric families of problems. The genericity analysis is based on results from differential geometry, in particular transversality theorems. ArticleDownload View … Read more

A New Class of Interior Proximal Methods for Optimization over the Positive Orthant

In this work we present a family of variable metric interior proximal methods for solving optimization problems under nonnegativity constraints. We define two algorithms, in the inexact and exact forms. The kernels are metrics generated by diagonal matrices in each iteration and the regularization parameters are conveniently chosen to force the iterates to be interior … Read more