Adaptive matrix algebras in unconstrained minimization
Linear Algebra and its Applications, vol. 471, pp. 544–568, 2015
In this paper we study adaptive $L(k)QN$ methods, involving special matrix algebras of low complexity, to solve general (non-structured) unconstrained minimization problems. These methods, which generalize the classical BFGS method, are based on an iterative formula which exploits, at each step, an ad hoc chosen matrix …