Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods in large scale nonconvex optimization
In this paper, we report data and experiments related to the research article entitled “An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization” by Caliciotti et. Al. [1]. In particular, in [1], large scale unconstrained optimization problems are considered by applying linesearch-based truncated Newton methods. In this framework, a key point is the reduction of the number of inner iterations needed, at each outer iteration, to approximately solving the Newton equation.