Objective acceleration for unconstrained optimization
Objective acceleration for unconstrained optimization is a scholarly work, published in 2018 in ''Numerical Linear Algebra with Applications''. The main subjects of the publication include uncertainty quantification, floating point, and mathematical optimization. The authors propose a natural modification to N‐GMRES, which significantly improves the performance in a testing environment originally used to advocate N‐GMRES.