In this paper we test different conjugate gradient (CG) methods for solving largescale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic ...

This course discusses basic convex analysis (convex sets, functions, and optimization problems), optimization theory (linear, quadratic, semidefinite, and geometric programming; optimality conditions ...

Researchers at Universidad Carlos III de Madrid (UC3M) have developed a set of innovative methods and algorithms that improve ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

Methods of cluster analysis based on maximizing or minimizing certain criteria are examined. The effect of adding a single point to the data casts light on the properties of the methods. Journal ...

How can components be designed for an optimal balance of minimal weight and maximum robustness? This is a challenge faced by ...