This book is on conjugate gradient methods for unconstrained optimization. The concept of
conjugacy was introduced by Magnus Hestenes and Garrett Birkhoff in 1936 in the context of …

Based on eigenvalue analyses, well-structured upper bounds for the condition number of
the scaled memoryless quasi-Newton updating formulae Broyden–Fletcher–Goldfarb …

Sažetak Using an extension of some previously proposed modified secant equations in the
Dai-Liao approach, a modified nonlinear conjugate gradient method is proposed. As …

Conjugate Gradient (CG) method was initially proposed for solving linear systems and
unconstrained minimization. The method is an excellent choice for solving optimization …

Conjugate Gradient (CG) method was initially suggested for solving linear system of
equation. Subsequently, the solution of a linear system is comparable to minimizing a …

Following the scaled conjugate gradient methods proposed by Andrei, we hybridize the
memoryless BFGS preconditioned conjugate gradient method suggested by Shanno and …

Following Andrei's approach of combining the conjugate gradient parameters convexly, a
hybridization of the Hestenes–Stiefel (HS) and Dai–Yuan conjugate gradient (CG) methods …

Taking advantage of the attractive features of Hestenes–Stiefel and Dai–Yuan conjugate
gradient methods, we suggest two globally convergent hybridizations of these methods …

In order to take advantage of the attractive features of the Hestenes–Stiefel and Dai–Yuan
conjugate gradient (CG) methods, we suggest two hybridizations of these methods based on …

There exist large varieties of conjugate gradient algorithms. In order to take advantage of the
attractive features of Liu and Storey (LS) and Conjugate Descent (CD) conjugate gradient …