Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

SIAM Journal on Numerical Analysis, Vol. 21, No. 2 (Apr., 1984), pp. 352-362 (11 pages) We characterize the class CG(s) of matrices A for which the linear system Ax = b can be solved by an s-term ...

There are three groups of optimization techniques available in PROC NLP. A particular optimizer can be selected with the TECH=name option in the PROC NLP statement. Since no single optimization ...

SIAM Journal on Numerical Analysis, Vol. 15, No. 6 (Dec., 1978), pp. 1247-1257 (11 pages) This paper studies the convergence of a conjugate gradient algorithm proposed in a recent paper by Shanno. It ...

First-order derivatives: n additional function calls are needed. Second-order derivatives based on gradient calls, when the "grd" module is specified (Dennis and Schnabel 1983): n additional gradient ...