A new nonmonotone line search algorithm is proposed and analyzed. In our scheme, we
require that an average of the successive function values decreases, while the traditional …

Since I started working in the area of nonlinear programming and, later on, variational
inequality problems, I have frequently been surprised to find that many algorithms, however …

Truncated-Newton methods are a family of methods for solving large optimization problems.
Over the past two decades, a solid convergence theory has been derived for the methods. In …

Classical optimizers play a crucial role in determining the accuracy and convergence of
variational quantum algorithms; leading algorithms use a near-term quantum computer to …

A nonmonotonic trust region method for unconstrained optimization problems is presented.
Although the method allows the sequence of values of the objective function to be …

The technique of nonmonotone line search has received many successful applications and
extensions in nonlinear optimization. This paper provides some basic analyses of the …

Dieses Buch bietet eine umfassende und aktuelle Darstellung des Themenbereichs"
Numerische Lösung unrestringierter Optimierungsaufgaben mit differenzierbarer …

The purpose of this paper is to discuss the potential of nonmonotone techniques for
enforcing convergence of unconstrained minimization algorithms from starting points distant …

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions
depending on the initial assumption sets. Parametric Empirical Bayes allows one to …

Recent developments in numerical methods for solving large differentiable nonlinear
optimization problems are reviewed. State-of-the-art algorithms for solving unconstrained …